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Integrating PCA and Streamline Information for History Matching Channelized Reservoirs

Fig. 2—The first step to identify facies, Egg example. Fig. 2d shows that the blue curve lies upon the black curve after applying CDF mapping. (a) Original facies; (b) reconstructed facies with PCA; (c) reconstructed facies with CDF-PCA; and (d) comparison of CDF between the three facies models.

Although principal-component analysis (PCA) has been applied widely to reduce the number of parameters characterizing a reservoir, its disadvantages are well-recognized. A work flow was proposed to integrate cumulative-distribution-function-based PCA (CDF-PCA) and streamline information for assisted history matching on a two-facies channelized reservoir. The CDF-PCA was developed to reconstruct reservoir models by use of only a few hundred principal components. It inherits the advantage of PCA to capture the main features or trends of spatial correlations among properties, and, more importantly, it can properly correct the smoothing effect of PCA.

Introduction

Both object-based and multipoint-­statistics-based models generate relatively more geologically realistic channel bodies compared with conventional two-point geostatistics-based techniques. However, conditioning such models to production data and correctly sampling the posterior probability distribution are challenging problems. One of the major challenges is that the number of para­meters to be tuned during history matching is too large to be handled effectively by available history-­matching work flows, especially when the adjoint gradient is unavailable. Another challenge is that the models obtained after history matching generally violate or distort the geological and geostatistical characteristics of the original or prior models.

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 170636, “Integration of Principal-Component Analysis and Streamline Information for the History Matching of Channelized Reservoirs,” by C. Chen, SPE, Shell International Exploration and Production; G. Gao, SPE, Shell Global Solutions US; J. Honorio, Massachusetts Institute of Technology; P. Gelderblom, SPE, Shell Global Solutions International; E. Jimenez, Qatar Shell GTL; and T. Jaakkola, Massachusetts Institute of Technology, prepared for the 2014 SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. The paper has not been peer reviewed.
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Integrating PCA and Streamline Information for History Matching Channelized Reservoirs

01 April 2015

Volume: 67 | Issue: 4

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