Uncertainty Quantification for History-Matching Problems
This paper presents a novel approach to generate approximate conditional realizations using the distributed Gauss-Newton (DGN) method together with a multiple local Gaussian approximation technique.
Field-Scale Assisted History Matching Using a Systematic Ensemble Kalman Smoother
This work presents a systematic and rigorous approach of reservoir decomposition combined with the ensemble Kalman smoother to overcome the complexity and computational burden associated with history matching field-scale reservoirs in the Middle East.
Drill and Learn: A Decision-Making Work Flow To Quantify Value of Learning
This paper presents a comparison of existing work flows and introduces a practically driven approach, referred to as “drill and learn,” using elements and concepts from existing work flows to quantify the value of learning (VOL).
Young Technology Showcase—Top-Down Modeling: A Shift in Building Full-Field Models for Mature Fields
Data-driven, or top-down, modeling uses machine learning and data mining to develop reservoir models based on measurements, rather than solutions of governing equations.
Bayesian-Style History Matching: Another Way To Underestimate Forecast Uncertainty?
This paper critically investigates the impact of using realistic, inaccurate simulation models. In particular, it demonstrates the risk of underestimating uncertainty when conditioning real-life models to large numbers of field data.
Streamline-Based History Matching for Multicomponent Compositional Systems
In this paper, the authors introduce a novel semianalytic approach to compute the sensitivity of the bottomhole pressure (BHP) data with respect to gridblock properties.
A Data-Driven Model for History Matching and Prediction
In this paper, the authors derive and implement an interwell numerical simulation model (INSIM) that can be used as a calculation tool to approximate the performance of a reservoir under waterflooding.
History Matching and Forecasting
History matching is only one part of something more comprehensive—reservoir modeling.
Model-Based Evaluation of Surveillance-Program Effectiveness With Proxies
This paper proposes a framework based on proxies and rejection sampling (filtering) to perform multiple history-matching runs with a manageable number of reservoir simulations.
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06 July 2018
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