{"id":"W2048478142","doi":"10.2118/166000-ms","title":"Improving the Estimation of Porosity and Permeability Distribution by Linking Basin Modelling to Diagenetic Evolution of Carbonate Reservoirs","year":2013,"lang":"en","type":"article","venue":"All Days","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Petrobras; CMG Reservoir Simulation Foundation","keywords":"Diagenesis; Geology; Carbonate; Structural basin; Basin modelling; Permeability (electromagnetism); Sedimentary depositional environment; Petrology; Petrophysics; Petroleum reservoir; Geochemistry; Geomorphology; Sedimentary basin; Porosity; Paleontology; Geotechnical engineering","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":[0.0005054255,0.0005720401,0.0003870481,0.0005395171,0.0002252425,0.0008263246,0.0006871527,0.0007635556,0.001015239],"category_scores_gemma":[0.002252355,0.0004223474,0.0006044933,0.0003791456,0.0002740358,0.0004614158,0.0004715588,0.0004536348,0.000153149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006118874,"about_ca_system_score_gemma":0.001122238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02409861,"about_ca_topic_score_gemma":0.01744331,"domain_scores_codex":[0.9998341,0.00005086481,0.00001503006,0.00004594595,0.00002924471,0.00002489505],"domain_scores_gemma":[0.9991547,0.0004970542,0.00007985395,0.0001025179,0.0001273319,0.00003864837],"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":[0.00001902903,0.00002923183,0.005183065,0.00001470776,0.00001745331,0.00001428099,0.00001740343,0.9864382,0.003706567,0.0001703647,0.0000372344,0.004352443],"study_design_scores_gemma":[0.000002467853,0.000004441344,0.0006297357,0.000001612191,0.00000221246,0.000002731524,0.000003518126,0.9981601,0.001052437,0.00008039898,0.00005764375,0.000002781862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8074188,0.00007785214,0.1869513,0.0001195194,0.00001796651,0.00008616987,0.0007331963,0.002362512,0.002232619],"genre_scores_gemma":[0.9694052,0.00002564365,0.03004186,0.000009514817,0.000002508441,0.00003369572,0.0001907309,0.00008556822,0.0002053707],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02409861,"threshold_uncertainty_score":0.04791665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008909672651572133,"score_gpt":0.1978190408854659,"score_spread":0.1889093682338937,"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."}}