{"id":"W2333669099","doi":"10.2118/175892-ms","title":"Estimating Effective Fracture Pore-Volume from Early Single-Phase Flowback Data and Relating It to Fracture Design Parameters","year":2015,"lang":"en","type":"article","venue":"","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Resources Canada","keywords":"Fracture (geology); Hydraulic fracturing; Volume (thermodynamics); Petroleum engineering; Closure (psychology); Well stimulation; Geology; Geotechnical engineering; Comminution; Materials science; Reservoir engineering; Thermodynamics; Petroleum","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005448301,0.0003417577,0.000380379,0.001706378,0.0001805108,0.0004383507,0.0005363454,0.0004030473,0.0004894919],"category_scores_gemma":[0.001621,0.0002209965,0.0002890682,0.0006376815,0.0002883408,0.0006527969,0.0002931514,0.0002495671,0.0001083982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004527561,"about_ca_system_score_gemma":0.0003731864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003701122,"about_ca_topic_score_gemma":0.004886055,"domain_scores_codex":[0.9997541,0.00004155989,0.00002639615,0.00004959214,0.0001015144,0.00002679667],"domain_scores_gemma":[0.9991152,0.0004996781,0.0001573186,0.00005565591,0.0001521926,0.00001997136],"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":[0.0004293573,0.0002187124,0.1907214,0.0003934556,0.0000747975,0.0002423596,0.0003012634,0.4496477,0.2308194,0.0009886983,0.000187457,0.1259754],"study_design_scores_gemma":[0.0000125377,0.0001322578,0.08847276,0.00002534001,0.00002156746,0.0001061756,0.0001257951,0.7901121,0.1197805,0.0008249456,0.0003369732,0.00004900885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9239029,0.00009383196,0.07500175,0.00001180771,0.000002463628,0.00003181348,0.0004359929,0.0001508023,0.0003686016],"genre_scores_gemma":[0.9865058,0.00003432766,0.01315428,0.000001831717,7.918899e-7,0.00002439664,0.0001770213,0.000008992224,0.00009251291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003701122,"threshold_uncertainty_score":0.007359147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03468430457630606,"score_gpt":0.2734385278126812,"score_spread":0.2387542232363751,"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."}}