{"id":"W3126026152","doi":"10.2118/205010-pa","title":"Simulated Annealing Algorithm-Based Inversion Model To Interpret Flow Rate Profiles and Fracture Parameters for Horizontal Wells in Unconventional Gas Reservoirs","year":2021,"lang":"en","type":"article","venue":"SPE Journal","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Inversion (geology); Algorithm; Geology; Inverse transform sampling; Synthetic data; Simulated annealing; Volumetric flow rate; Mechanics; Computer science; Seismology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0003895714,0.0004827763,0.0003550993,0.0002724864,0.0002900303,0.0003317299,0.0005026346,0.0005046271,0.001021398],"category_scores_gemma":[0.0007280372,0.000309195,0.0006102817,0.0002175166,0.0003097334,0.0004155098,0.0003146758,0.0004888705,0.0001735097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004986136,"about_ca_system_score_gemma":0.001106408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01449966,"about_ca_topic_score_gemma":0.009467317,"domain_scores_codex":[0.9998988,0.00003022274,0.000006551966,0.00002768406,0.00002178098,0.00001488233],"domain_scores_gemma":[0.99977,0.0001013219,0.00002529794,0.00001660157,0.0000769427,0.000009846053],"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":[0.00002198832,0.00001148691,0.0007531158,0.000009948734,0.00001299868,0.00001753739,0.00002478743,0.9894373,0.002778043,0.0006346796,0.00008811346,0.006209933],"study_design_scores_gemma":[9.876859e-7,0.000002804702,0.0000491971,5.229642e-7,9.955635e-7,0.000001045845,0.000001457434,0.9995804,0.0002561218,0.00007180308,0.00003381721,8.237942e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.119354,0.00009092138,0.8773947,0.000112856,0.0000196525,0.00004495457,0.00006515506,0.0004979076,0.002419892],"genre_scores_gemma":[0.8638849,0.00005925869,0.1336973,0.00003300455,0.000008239815,0.0001419499,0.0001304111,0.00005888104,0.001985896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01449966,"threshold_uncertainty_score":0.02883053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01128027932229178,"score_gpt":0.2402917779996184,"score_spread":0.2290114986773266,"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."}}