Frontiers in Earth Science,
Год журнала:
2024,
Номер
12
Опубликована: Дек. 12, 2024
Experimental
variogram
modelling
is
an
essential
process
in
geostatistics.
The
use
of
artificial
intelligence
(AI)
a
new
and
advanced
way
automating
experimental
modelling.
One
part
this
AI
approach
the
population
search
algorithms
to
fine-tune
hyperparameters
for
better
prediction
performing.
We
Bayesian
optimization
first
time
find
optimal
learning
parameters
more
precise
neural
network
regressor
goal
leverage
capability
consider
previous
regression
results
improve
output
using
three
variograms
as
inputs
one
training,
calculated
from
ore
grades
four
orebodies,
characterised
by
same
genetic
aspect.
In
comparison
architectures,
Bayesian-optimized
demonstrably
achieved
superior
Coefficient
determination
validation
78.36%.
This
significantly
outperformed
non-optimized
wide,
bilayer,
tri-layer
configurations,
which
yielded
32.94%,
14.00%,
−46.03%
determination,
respectively.
improved
reliability
demonstrates
its
superiority
over
traditional,
regressors,
indicating
that
incorporating
can
advance
modelling,
thus
offering
accurate
intelligent
solution,
combining
geostatistics
specifically
machine
PLoS ONE,
Год журнала:
2025,
Номер
20(5), С. e0324793 - e0324793
Опубликована: Май 22, 2025
The
reservoir
quality
of
the
Lower
Goru
Formation
is
highly
variable
due
to
its
heterogeneous
nature
influenced
by
sea
level
fluctuations
during
Early
Cretaceous
period.
This
study
applies
an
unsupervised
machine
learning
workflow,
integrating
Principal
Component
Analysis
(PCA)
for
dimensionality
reduction,
Self-Organizing
Maps
(SOM)
clustering,
and
fuzzy
classification
geological
labeling,
alongside
petrophysical
evaluation
cross-plot
analysis,
assess
impact
clay
minerals
on
in
NIM-Tay
block,
Indus
Basin,
Pakistan.
Petrophysical
analysis
delineates
a
potential
zone
(1455–1517
m)
characterized
13.9%
effective
porosity
27.3%
water
saturation.
first
four
principal
components
explain
approximately
90%
dataset
variance.
Electrofacies
distinguishes
facies—Impermeable
Reservoir,
Potential
Non-Reservoir,
Tight
Reservoir—each
corresponding
specific
mineral
assemblages.
Cross-plot
electrofacies
reveal
that
facies
dominated
chlorite
montmorillonite
preserve
(15%)
permeability
(888.87
mD),
whereas
kaolinite-rich
mixed-layer
significantly
reduce
quality.
provides
reproducible
scalable
framework
with
workflows,
offering
improved
characterization
not
only
Basin
but
also
similar
sandstone
reservoirs
globally.
Frontiers in Materials,
Год журнала:
2024,
Номер
11
Опубликована: Ноя. 1, 2024
This
study
investigates
countercurrent
air-water
two-phase
flow
in
vertical
pipes
with
inner
diameters
of
26
mm
and
44
a
height
2000
mm,
under
controlled
conditions
to
eliminate
heat
mass
transfer.
Cutting-edge
techniques
were
employed
measure
the
liquid
film
thickness
(δ)
entrainment
(e)
within
annular
pattern.
The
methodology
involved
systematic
comparative
analysis
experimental
results
against
established
models,
identifying
most
accurate
methods
for
predicting
behavior.
Specifically,
Schubring
et
al.
correlation
was
found
accurately
predict
e
pipes,
while
Wallis
more
pipes.
Additionally,
interfacial
shear
stress
analyzed,
confirming
high
precision
δ
parameters.
research
enhances
understanding
by
providing
reliable
estimation
different
pipe
emphasizes
significance
determining
stress.
Key
findings
include
identification
models
sizes
addressing
challenges
measuring
conditions.
study’s
novelty
lies
its
comprehensive
existing
leading
improved
predictions
dynamics
thereby
contributing
valuable
insights
into
behavior
geosciences
environmental
engineering.
