Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a
  Case Study   Virtual flow meters, mathematical models predicting production flow rates in
petroleum assets, are useful aids in production monitoring and optimization.
Mechanistic models based on first-principles are most common, however,
data-driven models exploiting patterns in measurements are gaining popularity.
This research investigates a hybrid modeling approach, utilizing techniques
from both the aforementioned areas of expertise, to model a well production
choke. The choke is represented with a simplified set of first-principle
equations and a neural network to estimate the valve flow coefficient.
Historical production data from the petroleum platform Edvard Grieg is used for
model validation. Additionally, a mechanistic and a data-driven model are
constructed for comparison of performance. A practical framework for
development of models with varying degree of hybridity and stochastic
optimization of its parameters is established. Results of the hybrid model
performance are promising albeit with considerable room for improvements.

35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th