Use of a Probabilistic and Multi-Objective History Matching for Uncertainty Reduction for the Norne Benchmark Case

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Abstract History matching integrated with uncertainty reduction is a key process in the closed loop reservoir development and management methodology which is used for decision analysis related to the development & management of petroleum fields. Despite developments over the last decades in history matching & uncertainty analysis, the challenge of capturing complex interaction among several attributes and several reservoir responses acting simultaneously for complex models still remains. This paper describes the use of a probabilistic and multi-objective history matching integrated with uncertainty reduction as a systematic and iterative process for obtaining a set of reservoir models that honors dynamic data in a complex field case. The methodology is an iterative process that simultaneously matches different objective functions, one for each well production profile. The procedure uses a re-characterization step, where the uncertainties of the attributes (represented by their probability density functions) are updated using indicators that show global and local problems and a correlation matrix to capture the interaction between several reservoir uncertainties and the different objective functions. The methodology was applied to the Norne Field benchmark case considering production data up to 2001 and the remaining part of the provided history is used to estimate the quality of production forecast. The major benefit derived from the application of the methodology was the identification of global and local problems. The initial reservoir models presented high discrepancies between simulated and observed data. The use of independent objective functions in conjunction with the concise plot that is based on the normalized quadratic error of each production data highlighted when new parametrization of the reservoir was necessary. New reservoir attributes were added, such as separated permeability curves for each reservoir formation and new gas permeability curves that better describe the fluid behavior. The initial number of uncertain attributes was twenty seven; the correlation matrix clearly showed which one of those had major influence on the results. Some attributes with significant impact in the study were water-oil and gas-oil contact and faults transmissibility. We updated the probability of the most influencing attributes in order to identify the uncertain levels that improved the history match results. The methodology integrated the process of history matching with uncertainty analysis, addressing both processes simultaneously for a complex case. The methodology was effective and simple to use, even in the complex case study where the reservoir characterization is important.