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.
Don't miss out on the latest technology delivered to your email weekly. Sign up for the JPT newsletter. If you are not logged in, you will receive a confirmation email that you will need to click on to confirm you want to receive the newsletter.
09 October 2018
11 October 2018
08 October 2018