Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysis of Geometric Selection of the Data-Error Covariance Inflation
  for ES-MDA   The ensemble smoother with multiple data assimilation (ES-MDA) is becoming a
popular assisted history matching method. In its standard form, the method
requires the specification of the number of iterations in advance. If the
selected number of iterations is not enough, the entire data assimilation must
be restarted. Moreover, ES-MDA also requires the selection of data-error
covariance inflations. The typical choice is to select constant values.
However, previous works indicate that starting with large inflation and
gradually decreasing during the data assimilation steps may improve the quality
of the final models.
  This paper presents an analysis of the use of geometrically decreasing
sequences of the data-error covariance inflations. In particular, the paper
investigates a recently introduced procedure based on the singular values of a
sensitivity matrix computed from the prior ensemble. The paper also introduces
a novel procedure to select the inflation factors. The performance of the data
assimilation schemes is evaluated in three reservoir history-matching problems
with increasing level of complexity. The first problem is a small synthetic
case which illustrates that the standard ES-MDA scheme with constant inflation
may result in overcorrection of the permeability field and that a geometric
sequence can alleviate this problem. The second problem is a recently published
benchmark and the third one is a field case with real production data. The data
assimilation schemes are compared in terms of a data-mismatch and a
model-change norm. The first norm evaluates the ability of the models to
reproduce the observed data. The second norm evaluates the amount of changes in
the prior model. The results indicate that geometric inflations can generate
solutions with good balance between the two norms.

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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-alg
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
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The categories of this paper are: dg-ga
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The categories of this paper are: atom-ph
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The categories of this paper are: cs
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The categories of this paper are: cond-mat
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The categories of this paper are: ao-sci
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-th
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The categories of this paper are: bayes-an