{"id":"W2766472206","doi":"10.1144/petgeo2017-017","title":"Micropore network modelling from 2D confocal imagery: impact on reservoir quality and hydrocarbon recovery","year":2017,"lang":"en","type":"article","venue":"Petroleum Geoscience","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Saudi Aramco; CMG Reservoir Simulation Foundation; Houston Advanced Research Center","keywords":"Geology; Telmatology; Igneous petrology; Metamorphic petrology; Geobiology; Economic geology; Environmental geology; Gemology; Petroleum engineering; Regional geology; Microporous material; Racing slick; Petrology; Quality (philosophy); Hydrogeology; Geochemistry; Engineering geology; Volcanism; Paleontology; Geotechnical engineering; Tectonics; Engineering; Chemical 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":[0.0006053947,0.0006355715,0.0003436335,0.0005865649,0.0002812723,0.001170869,0.0007009408,0.00107442,0.001184706],"category_scores_gemma":[0.001768783,0.0003233856,0.0006263374,0.0003951683,0.0003244532,0.0009715673,0.0004876848,0.0005175748,0.0002509728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007798508,"about_ca_system_score_gemma":0.001142413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0197338,"about_ca_topic_score_gemma":0.02085258,"domain_scores_codex":[0.9998313,0.00003323212,0.00001166239,0.00004698268,0.00004849062,0.00002826127],"domain_scores_gemma":[0.9992697,0.0003924357,0.00008611078,0.00005991773,0.0001463,0.00004559066],"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":[0.0001587047,0.00009899175,0.008974046,0.000159227,0.00005155577,0.0001132624,0.000142166,0.9432628,0.02587774,0.001053656,0.0003782318,0.01972956],"study_design_scores_gemma":[0.000003141019,0.00001009846,0.0005643874,0.000006096049,0.000004016559,0.00001484262,0.0000181684,0.9959571,0.003113267,0.0001558981,0.0001444412,0.000008461217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7979236,0.0003841141,0.1936564,0.000386639,0.00003739849,0.0001420767,0.001563806,0.002114514,0.003791523],"genre_scores_gemma":[0.9176552,0.0002763559,0.08025566,0.00003988867,0.000006649214,0.00006285065,0.0007288386,0.0001542424,0.0008203894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0197338,"threshold_uncertainty_score":0.03923786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03127124387033603,"score_gpt":0.2831901532304878,"score_spread":0.2519189093601518,"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."}}