{"id":"W2007283644","doi":"10.2118/163814-ms","title":"Prediction of SRV and Optimization of Fracturing in Tight Gas and Shale Using a Fully Elasto-Plastic Coupled Geomechanical Model","year":2013,"lang":"en","type":"article","venue":"SPE Hydraulic Fracturing Technology Conference","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Hydraulic fracturing; Tight gas; Microseism; Shear (geology); Shale gas; Geology; Oil shale; Mechanics; Ultimate tensile strength; Petroleum engineering; Materials science; Seismology; Physics; Petrology; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001489885,0.0002798937,0.0005457222,0.0007955171,0.0000601063,0.00002965424,0.0002241821,0.000449902,0.00006623473],"category_scores_gemma":[0.0001559984,0.0002738127,0.0000477979,0.0003726032,0.0002307964,0.0002961171,0.0001474744,0.0005172755,0.000002246411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006525663,"about_ca_system_score_gemma":0.00004091699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002825433,"about_ca_topic_score_gemma":0.00004601682,"domain_scores_codex":[0.9984377,0.00002244793,0.0005959537,0.000377951,0.0002034133,0.0003625086],"domain_scores_gemma":[0.9991697,0.0001056453,0.0001707738,0.0003605522,0.0001018038,0.00009149714],"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":[0.00001065719,0.00003267195,0.001086469,0.0001856654,0.00005877243,0.000005440741,0.0001883166,0.9755617,0.02136196,0.00003589411,0.00000380322,0.001468652],"study_design_scores_gemma":[0.0005230612,0.00005186459,0.001686377,0.0002693554,0.00005637495,0.00002513094,0.0001046752,0.9753888,0.01980036,0.001889409,0.000006170873,0.0001984067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6659192,0.0002506802,0.3332532,0.0001048778,0.00004555956,0.0001664739,0.000004973632,0.0001527231,0.0001022092],"genre_scores_gemma":[0.98597,0.0004006178,0.01352662,0.000008223851,0.00001876715,0.00002396442,0.000007287213,0.00003514136,0.000009436264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3200507,"threshold_uncertainty_score":0.9999714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290182558607701,"score_gpt":0.2000373087415777,"score_spread":0.1871354831555007,"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."}}