Integration of Artificial Intelligence and Advanced Optimization Techniques for Continuous Gas Lift under Restricted Gas Supply: A Case Study
Digital Chemical Engineering,
Год журнала:
2025,
Номер
14, С. 100220 - 100220
Опубликована: Фев. 1, 2025
Язык: Английский
Choke Flow Oil Rate Through Surface Data: Modeling via Rigorous methods
Flow Measurement and Instrumentation,
Год журнала:
2025,
Номер
unknown, С. 102911 - 102911
Опубликована: Апрель 1, 2025
Язык: Английский
Development of a non-intrusive ROM for 5 × 5 rod bundles of PWR using small sample data
Annals of Nuclear Energy,
Год журнала:
2025,
Номер
217, С. 111347 - 111347
Опубликована: Март 9, 2025
Язык: Английский
Improving iron ore blending using radial basis function neural network (RBFNN) for enhanced steel production in Egypt
Arabian Journal of Geosciences,
Год журнала:
2025,
Номер
18(4)
Опубликована: Март 25, 2025
Язык: Английский
A new interpolation model for explicit coupling of reservoir and surface facilities using flow tables
Fuel,
Год журнала:
2025,
Номер
395, С. 135253 - 135253
Опубликована: Апрель 5, 2025
Язык: Английский
Audio analysis with convolutional neural networks and boosting algorithms tuned by metaheuristics for respiratory condition classification
Journal of King Saud University - Computer and Information Sciences,
Год журнала:
2024,
Номер
unknown, С. 102261 - 102261
Опубликована: Дек. 1, 2024
Язык: Английский
MobVGG: Ensemble Technique for Birds and Drones Prediction
Heliyon,
Год журнала:
2024,
Номер
10(21), С. e39537 - e39537
Опубликована: Окт. 21, 2024
Язык: Английский
In-depth exploration and application of fracturing construction curves in fractured tight sandstone reservoirs of the Tarim Basin
Frontiers in Earth Science,
Год журнала:
2024,
Номер
12
Опубликована: Дек. 24, 2024
Fractured
tight
sandstone
reservoirs
are
representative
in
the
Tarim
Basin,
characterized
by
development
of
natural
fractures
and
diverse
interaction
modes
between
artificial
fractures.
The
complex
shape
construction
pressure
curves
during
fracturing
makes
it
difficult
for
existing
fracture
extension
diagnosis
methods
to
provide
effective
guidance.
To
thoroughly
explore
information
contained
accurately
characterize
hydraulic
parameters,
this
study
proposes
a
dynamic
bottomhole
net
calculation
method
based
on
real-time
data,
allowing
more
precise
correction
pressure.
Subsequently,
mode
recognition
mechanism
fractured
is
established,
identifying
five
extension:
activation
fractures,
restricted
extension,
communication
with
vertical
penetration
concept
post-fracturing
network
index
introduced,
leading
comprehensive
diagnosing
recognizing
suitable
reservoirs.
Field
case
studies
indicate
that:
(1)
ability
activate
form
closely
related
pressure;
(2)
when
curve
exhibits
periodic
trends,
within
reservoir
may
branch
redirect,
forming
multi-stage
fractures;
(3)
higher
corresponds
unimpeded
flow
capacity,
indicating
better
production
enhancement
effects.
conclusion
suggests
that
can
enhance
potential
significant
guiding
adjustments
field
operations.
Язык: Английский
A Novel Technique in Determining Mud Cake Permeability in SiO2 Nanoparticles and KCl Salt Water Based Drilling Fluid using Deep Learning Algorithm
International Journal of Petroleum Technology,
Год журнала:
2024,
Номер
11, С. 29 - 39
Опубликована: Окт. 28, 2024
The
permeability
of
the
mud
cake
formed
at
formation-wellbore
interface
is
an
important
factor
in
designing
water-based
drilling
fluids.
This
study
presents
a
novel
approach
to
utilizing
experimental
thixotropic
and
rheological
parameters
polymeric
fluids
having
varying
concentrations
SiO2
nanoparticles
KCl
salt.
A
fully
connected
feed-forward
multi-layered
neural
network,
more
commonly
known
as
Multilayer
Perceptron
(MLP)
was
developed
predict
using
input
such
&
concentration,
differential
pressure,
temperature,
thickness,
API
LPLT
HPHT
filter
loss
volume
spurt
volume.
results
suggested
that
model
effectively
determined
based
on
WBDF
mentioned
above.
converged
global
minima,
minimizing
function
Gradient
descent
algorithm.
higher
Coefficient
Determination
(R2)
value
i.e.,
0.8781,
lesser
Root
Mean
Square
Error
(RMSE)
0.04378
indicates
accuracy
model.
Pearson’s
Correlation
obtained
via
heatmap
strongly
influenced
by
pressure
followed
volume,
temperature.
Previous
similar
studies
have
focused
machine
learning
algorithms,
this
utilized
robust
deep
algorithm
network
simultaneously
combined
effects
salt
permeability,
offering
unprecedented
level
predicting
key
performance
Язык: Английский
Assessment of Tail-Cutting in Frozen Albacore (Thunnus alalunga) Through Ultrasound Inspection and Chemical Analysis
Foods,
Год журнала:
2024,
Номер
13(23), С. 3860 - 3860
Опубликована: Ноя. 29, 2024
Fat
content
is
the
main
criterion
for
evaluating
albacore
quality.
However,
no
reports
exist
on
accuracy
of
tail-cutting
method,
a
method
used
to
assess
fat
albacore.
Here,
we
evaluated
this
by
comparing
it
with
chemical
analysis
and
ultrasound
inspection.
We
measured
actual
in
using
compared
results
those
obtained
method.
Significant
discrepancies
(99%
CI,
t-test)
were
observed
among
samples.
Using
as
ground
truth,
from
two
different
companies
was
70.0%
company
A
51.9%
B.
An
inspection
revealed
that
higher
reduced
amplitude
signals
statistical
significance
t-test).
Finally,
machine
learning
algorithms
enforce
The
best
combination
algorithm
achieved
an
84.2%
selecting
fat-rich
albacore,
which
better
than
(73.6%).
Our
findings
suggested
could
be
valuable
non-destructive
estimating
achieving
traditional
Язык: Английский