Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computational Intelligence for Deepwater Reservoir Depositional
  Environments Interpretation   Predicting oil recovery efficiency of a deepwater reservoir is a challenging
task. One approach to characterize a deepwater reservoir and to predict its
producibility is by analyzing its depositional information. This research
proposes a deposition-based stratigraphic interpretation framework for
deepwater reservoir characterization. In this framework, one critical task is
the identification and labeling of the stratigraphic components in the
reservoir, according to their depositional environments. This interpretation
process is labor intensive and can produce different results depending on the
stratigrapher who performs the analysis. To relieve stratigrapher's workload
and to produce more consistent results, we have developed a novel methodology
to automate this process using various computational intelligence techniques.
Using a well log data set, we demonstrate that the developed methodology and
the designed workflow can produce finite state transducer models that interpret
deepwater reservoir depositional environments adequately.

27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
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The categories of this paper are: q-fin
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
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The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn