{"id":"W2041378062","doi":"10.2118/168968-ms","title":"Simulation of Liquid-Rich Shale Gas Reservoirs with Heavy Hydrocarbon Fraction Desorption","year":2014,"lang":"en","type":"article","venue":"SPE Unconventional Resources Conference","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures; Shell Canada","keywords":"Oil shale; Hydrocarbon; Petroleum engineering; Desorption; Oil shale gas; Adsorption; Natural gas; Chemistry; Porosity; Volume (thermodynamics); Organic matter; Fossil fuel; Fraction (chemistry); Unconventional oil; Geology; Chromatography; Organic chemistry; Thermodynamics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002864969,0.0005487661,0.0006780447,0.0006181075,0.0006096552,0.0007676427,0.0009718483,0.001616272,0.003053574],"category_scores_gemma":[0.001317028,0.0003633577,0.0007500577,0.0006465807,0.0007687133,0.0005155246,0.0006290537,0.0006652267,0.0001835742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001153645,"about_ca_system_score_gemma":0.001191599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02736629,"about_ca_topic_score_gemma":0.01406568,"domain_scores_codex":[0.9998466,0.00002946147,0.000007950118,0.00002169648,0.00003525044,0.00005894319],"domain_scores_gemma":[0.9990935,0.0005409385,0.00007792383,0.00004627762,0.0001410064,0.0001003294],"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":[0.0001007109,0.00008971355,0.003651917,0.00002858378,0.00001415106,0.0001106116,0.00002608404,0.993143,0.001591156,0.0004415309,0.0001137009,0.0006889075],"study_design_scores_gemma":[0.00001982258,0.00003846894,0.0006490832,0.000003599289,0.000003567568,0.000006305429,0.00002910134,0.998333,0.0007143566,0.00007821162,0.0001202279,0.000004200225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899822,0.00006354933,0.003051227,0.0001206638,0.00001552755,0.00004886299,0.0006444483,0.0001268101,0.00594675],"genre_scores_gemma":[0.9967278,0.0000401364,0.001782101,0.00002085053,0.000003036708,0.00004900854,0.0003671615,0.00001901047,0.0009907689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02736629,"threshold_uncertainty_score":0.05441397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01834566666752262,"score_gpt":0.2345917491053717,"score_spread":0.216246082437849,"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."}}