{"ok":true,"trend":{"id":571830,"platform":"news","region":"global","key":"hybrid physics/ml framework for virtual flowmetering optimizes production","title":"Hybrid Physics/ML Framework for Virtual Flowmetering Optimizes Production","url":"https://news.google.com/rss/articles/CBMipwFBVV95cUxNNEhRZEtqcW5sNnBVZEpHYXFLWmdqbXk0WFp1My1jeTJBRFdjSmNxVVhlUF9jM25WaXZiTW16bk5kS0U3LU9WRXpTVUlYUjFQQVhUcU9KOW43VzRfOVVqRTQ1U2pkMkZBM1Mzc0dPYnVaWmpCcEgyeXRRQjY5QWVaQXIySEMtUmJ3dk9pYkQ2YUpNM1lqZVJqNVBDSWFiWFZhdS1kLXF3UQ?oc=5","first_seen":"2026-10-01T05:27:52.154288Z","last_seen":"2026-10-02T00:38:21.280707Z","last_rank":36,"peak_rank":1,"last_volume":null,"peak_volume":0,"seen_count":15,"score":0.54140625,"category_hint":"physics","section":"science","category":"physics","summary":"The Journal of Petroleum Technology reports on a hybrid framework combining physics-based models with machine learning for virtual flowmetering, aimed at optimizing oil and gas production. Virtual flowmeters estimate flow rates from existing sensor data, reducing the need for costly physical meters. The approach is presented as a way to improve accuracy and reliability in production monitoring across wells.","why":"Operators are increasingly adopting machine learning tools to cut metering costs and improve production monitoring.","tone":"neutral","entities":["Journal of Petroleum Technology"],"summarized_at":"2026-10-01T23:33:46.843872Z","meta":{"via":"scan","lang":"en","term":"physics","source":"JPT Homepage","published":"Thu, 01 Oct 2026 05:06:10 GMT"},"nw":null,"promo":null,"kind":null,"importance":null,"hidden":false,"hide_reason":null,"judged_at":null,"title_en":"Hybrid Physics/ML Framework Improves Virtual Flowmetering","section_name":"Science","category_name":"Physics","timeline":[{"captured_at":"2026-10-01T05:27:52.154288Z","rank":1,"volume":null},{"captured_at":"2026-10-01T06:49:54.166426Z","rank":2,"volume":null},{"captured_at":"2026-10-01T08:12:17.848293Z","rank":3,"volume":null},{"captured_at":"2026-10-01T09:34:30.487849Z","rank":3,"volume":null},{"captured_at":"2026-10-01T10:56:34.370465Z","rank":3,"volume":null},{"captured_at":"2026-10-01T12:19:03.113724Z","rank":4,"volume":null},{"captured_at":"2026-10-01T13:41:17.577157Z","rank":5,"volume":null},{"captured_at":"2026-10-01T15:03:17.543178Z","rank":6,"volume":null},{"captured_at":"2026-10-01T16:25:19.577535Z","rank":14,"volume":null},{"captured_at":"2026-10-01T17:47:16.955585Z","rank":23,"volume":null},{"captured_at":"2026-10-01T19:09:40.756001Z","rank":29,"volume":null},{"captured_at":"2026-10-01T20:32:21.967067Z","rank":32,"volume":null},{"captured_at":"2026-10-01T21:54:20.810849Z","rank":34,"volume":null},{"captured_at":"2026-10-01T23:16:23.480462Z","rank":35,"volume":null},{"captured_at":"2026-10-02T00:38:21.280707Z","rank":36,"volume":null}],"posts":[{"platform":"news","url":"https://news.google.com/rss/articles/CBMipwFBVV95cUxNNEhRZEtqcW5sNnBVZEpHYXFLWmdqbXk0WFp1My1jeTJBRFdjSmNxVVhlUF9jM25WaXZiTW16bk5kS0U3LU9WRXpTVUlYUjFQQVhUcU9KOW43VzRfOVVqRTQ1U2pkMkZBM1Mzc0dPYnVaWmpCcEgyeXRRQjY5QWVaQXIySEMtUmJ3dk9pYkQ2YUpNM1lqZVJqNVBDSWFiWFZhdS1kLXF3UQ?oc=5","author":"JPT Homepage","title":"Hybrid Physics/ML Framework for Virtual Flowmetering Optimizes Production","snippet":null,"posted_at":"2026-10-01T05:03:30Z","likes":null}],"elsewhere":[],"window":"7d"}}