Invention Application
- Patent Title: NUCLEAR MAGNETIC RESONANCE (NMR) FLUID SUBSTITUTION USING MACHINE LEARNING
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Application No.: US17514654Application Date: 2021-10-29
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Publication No.: US20230133700A1Publication Date: 2023-05-04
- Inventor: Songhua Chen , Wei Shao
- Applicant: Halliburton Energy Services, Inc.
- Applicant Address: US TX Houston
- Assignee: Halliburton Energy Services, Inc.
- Current Assignee: Halliburton Energy Services, Inc.
- Current Assignee Address: US TX Houston
- Main IPC: G01V3/32
- IPC: G01V3/32 ; G01N24/08 ; G01R33/50 ; G01V3/38

Abstract:
System and methods for nuclear magnetic resonance (NMR) fluid substitution are provided. NMR logging measurements of a reservoir rock formation are acquired. Fluid zones within the reservoir rock formation are identified based on the acquired measurements. The fluid zones include water zones comprising water-saturated rock and at least one oil zone comprising rock saturated with multiphase fluids. Water zones having petrophysical characteristics matching those of the oil zone(s) within the formation are selected. NMR responses to multiphase fluids resulting from a displacement of water by hydrocarbon in the selected water zones are simulated. A synthetic dataset including NMR T2 distributions of multiphase fluids is generated based on the simulation. The synthetic dataset is used to train a machine learning (ML) model to substitute NMR T2 distributions of multiphase fluids with those of water. The trained ML model is applied to the NMR logging measurements acquired for the oil zone(s).
Public/Granted literature
- US11828901B2 Nuclear magnetic resonance (NMR) fluid substitution using machine learning Public/Granted day:2023-11-28
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