{"id":"W2887575641","doi":"10.1016/j.petrol.2018.08.023","title":"Analytical modeling of linear flow in single-phase tight oil and tight gas reservoirs","year":2018,"lang":"en","type":"article","venue":"Journal of Petroleum Science and Engineering","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tight gas; Petroleum engineering; Flow (mathematics); Compressibility; Constant (computer programming); Mechanics; Tight oil; Reservoir engineering; Drawdown (hydrology); Geology; Oil shale; Geotechnical engineering; Petroleum; Computer science; Hydraulic fracturing; Aquifer; Physics; Groundwater","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009831365,0.0001366905,0.0003261195,0.0007891906,0.00006633459,0.00005318514,0.0002173705,0.00006206337,0.000008499357],"category_scores_gemma":[0.0002223449,0.000110483,0.00005683186,0.0006263704,0.0001665807,0.0004225343,0.00004903607,0.0002824237,8.920141e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007779895,"about_ca_system_score_gemma":0.00004663417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001304092,"about_ca_topic_score_gemma":0.000009903415,"domain_scores_codex":[0.9986189,0.000009167479,0.0004624897,0.0001437049,0.0004513273,0.0003143822],"domain_scores_gemma":[0.9993671,0.00004301424,0.00005585769,0.0001389724,0.0001767734,0.0002182551],"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":[0.00001426161,0.00002599818,0.000163418,0.00007263899,0.00002455479,0.00002323807,0.0003168623,0.9736511,0.02339461,0.000006100375,0.00001626375,0.002290938],"study_design_scores_gemma":[0.0004806881,0.0001227887,0.0001269302,0.0001953608,0.00002722378,0.0000551418,0.00008477771,0.9945278,0.003780009,0.00000906154,0.000472536,0.0001176983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841293,0.0006467002,0.01432816,0.0001686524,0.000163498,0.000007258209,0.000001110514,0.00001802055,0.0005372736],"genre_scores_gemma":[0.9955758,0.0003662609,0.003798805,0.000006065453,0.0002183424,4.173805e-7,2.024654e-7,0.00001357857,0.00002051228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02087667,"threshold_uncertainty_score":0.4505364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276500563788858,"score_gpt":0.2406750848750188,"score_spread":0.2279100792371302,"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."}}