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History Matching and Uncertainty Quantification Using Produced Water Chemistry

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History Matching and Uncertainty Quantification Using Produced Water Chemistry
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  History Matching and Uncertainty Quantification Using Produced Water Chemistry By Obinna Nwafor Supervisor - Oscar Vazquez  CONTENT  Automatic History Matching Problem Statement Water Tracers Particle Swarm Optimization Bayesian Framework for Uncertainty Quantification Neighbourhood Approximation Bayes PUNQS3 Model 2 Parameterisation History Data Results  –  Pareto Front Advance and Misfits Results  –  Quality of History Match Results  –  Uncertainty in Forecasts Conclusion   AUTOMATIC HISTORY MATCH Reservoir Model Calibration Reservoir Properties Required Observations - Production Data; Prior data Inversion of Data into Properties Automatic History Matching as Mathematical Optimization Misfit Functions as Objective Functions Minimization Results History Match Non-Unique Solutions Value of Improved History Matching Selection of Field Development Methods Facility Sizing Risk Management Profits 3  PROBLEM STATEMENT INJECTED SEA WATER PRODUCTION DATA CAN IMPROVE HISTORY MATCHING Potentials ã Complementary Information on Reservoir Flow Paths ã Previous studies suggest potentials INVESTIGATE EFFECT OF INJECTED SEA WATER PRODUCTION DATA OBTAINED USING NATURAL TRACERS ON HISTORY MATCH AND UNCERTAINTY Task: ã Obtain Sea Water Production Data Using Natural Water Tracer (Cl -  ion) ã Determine if improvements occur in history match misfits ã Determine if improvements occur in uncertainty estimation CONSTRUCTED AS TWO CASES OF HISTORY MATCHING Investigation: ã Case 1: Involves Constraint by Injected Sea Water Tracer Produced Data (SWTP) ã Case 2: Excludes the Injected Sea Water Tracer Production Data (NSWTP) ã Case-C: Control Case  –  repeats case 1(SWTP) 4
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