Invention Grant
- Patent Title: Model-constrained multi-phase virtual flow metering and forecasting with machine learning
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Application No.: US17571907Application Date: 2022-01-10
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Publication No.: US12085687B2Publication Date: 2024-09-10
- Inventor: Tao Lin , Weichang Li , Muhammad Arsalan , Abdulla Al Sarraf
- Applicant: Saudi Arabian Oil Company
- Applicant Address: SA Dhahran
- Assignee: Saudi Arabian Oil Company
- Current Assignee: Saudi Arabian Oil Company
- Current Assignee Address: SA Dhahran
- Agency: Fish & Richardson P.C.
- Main IPC: G01V20/00
- IPC: G01V20/00 ; G06F30/27 ; G06F30/28 ; G06N20/00 ; G06F113/08

Abstract:
A computer-implemented method for constrained multi-phase virtual flow metering and forecasting is described. The method includes predicting instantaneous flow rates and forecasting future target flow rates and well dynamics. The method includes constructing a virtual sensing model trained using forecasted target flow rates and well dynamics. The method includes building a constrained forecasting model by combining unconstrained flow forecasting models, well dynamics models, and virtual sensing models, wherein the constrained forecasting model forecasts multi-phase flow rates.
Public/Granted literature
- US20230221460A1 Model-Constrained Multi-Phase Virtual Flow Metering and Forecasting with Machine Learning Public/Granted day:2023-07-13
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