Unconventional/complex reservoirs

Machine-Learning and Physics-Based Models Compared in Downhole Pressure Prediction in Deepwater Reservoirs

In this work, novel physics-based models and machine-learning models are presented and compared for estimating permanent-downhole-gauge measurements.

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Pressure measurements from permanent downhole gauges (PDHGs) during extended shut-ins often are used for model calibration and reserves estimation in deepwater gas reservoirs. A key challenge in practical operation has been the failure of PDHGs within the first few years of operation. To overcome this challenge, modeling solutions have been developed to enable accurate bottomhole well pressures to be calculated. In the complete paper, novel physics-based models and machine-learning (ML) models are presented and compared for estimating PDHG measurement from wellhead measurements.

Introduction

One way to predict PDHG shut-in pressure is with a full-physics wellbore simulator.

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