{"id":"W4404013456","doi":"10.2118/221957-ms","title":"Enhancing Efficiency and Sustainability in Offshore Oil and Gas Operations through Digital Twin and AI Technology: A Practitioner's View","year":2024,"lang":"en","type":"article","venue":"","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Sustainability; Submarine pipeline; Fossil fuel; Petroleum engineering; Offshore oil and gas; Computer science; Business; Manufacturing engineering; Engineering; Waste management","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":[0.002515753,0.0003907554,0.0003114713,0.0007017617,0.0003537678,0.00331467,0.0008766973,0.001818603,0.002190878],"category_scores_gemma":[0.002111856,0.0001781843,0.0002703879,0.0009584265,0.002103114,0.003509062,0.001492704,0.001806862,0.0004201839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008925501,"about_ca_system_score_gemma":0.001198104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008880342,"about_ca_topic_score_gemma":0.0009527117,"domain_scores_codex":[0.9993581,0.0002683472,0.00002633617,0.00008679252,0.0002219864,0.00003852412],"domain_scores_gemma":[0.9985754,0.000829411,0.00005625408,0.0001254313,0.0003362339,0.00007710337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008647512,0.0002509444,0.002284637,0.001179904,0.00004559927,0.0005089201,0.001769077,0.04599441,0.01350869,0.5367218,0.004474327,0.3931752],"study_design_scores_gemma":[0.00004920692,0.0007547154,0.00135287,0.001302398,0.00007933936,0.001159052,0.006957709,0.3242452,0.02403303,0.3901377,0.2498502,0.00007854668],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07117642,0.02641425,0.748758,0.03155978,0.0005510245,0.00007921661,0.0000389553,0.000401689,0.1210208],"genre_scores_gemma":[0.7489931,0.03008504,0.2025903,0.001460599,0.0003671463,0.0000624692,0.00002572518,0.0000650307,0.01635069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00331467,"threshold_uncertainty_score":0.01330471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004642571249827022,"score_gpt":0.2484826802648023,"score_spread":0.2438401090149752,"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."}}