Overview and outlook of thermal processes in geothermal energy extraction
Applied Thermal Engineering,
Год журнала:
2025,
Номер
unknown, С. 126329 - 126329
Опубликована: Март 1, 2025
Язык: Английский
Current status and construction scheme of smart geothermal field technology
Petroleum Exploration and Development,
Год журнала:
2024,
Номер
51(4), С. 1035 - 1048
Опубликована: Авг. 1, 2024
Язык: Английский
A theoretical model and experimental investigation of fluid flow in granite rough fracture
Physics of Fluids,
Год журнала:
2025,
Номер
37(1)
Опубликована: Янв. 1, 2025
The
fissure
serves
as
the
primary
flow
channel
within
a
rock
mass
and
plays
crucial
role
in
behavior
of
fractures.
geometric
features
fracture,
combined
with
nonlinear
phenomena,
complicate
process
significantly.
To
investigate
fluid
characteristics
fractures
rough
granite,
this
study
presents
an
improved
mathematical
model
that
correlates
rock's
true
surfaces
pressure
variations
during
flow.
effectively
describes
relationship
between
drop
velocity.
fluids
fractures,
proposes
based
on
Forchheimer's
law
to
describe
rate.
accounts
for
two
conditions:
linear
low
Reynolds
number
region
higher
region.
Hydraulic
tests
were
conducted
three
granites
varying
fracture
geometries,
validating
model's
accuracy.
Subsequently,
granite
are
quantitatively
described,
underlying
mechanisms
illustrated
through
analysis
experimental
data.
Finally,
empirical
formula
was
established
critical
geometrical
characterization
parameters
clear
physical
significance.
These
results
enhance
understanding
contribute
numerical
simulation
processes.
Язык: Английский
Optimization of hot dry rock heat extraction performance considering the interaction of multi-mineral component water-rock reactions and fracture roughness
Energy,
Год журнала:
2025,
Номер
unknown, С. 135089 - 135089
Опубликована: Фев. 1, 2025
Язык: Английский
Review of artificial intelligence applications in geothermal energy extraction from hot dry rock
Deep Underground Science and Engineering,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 9, 2025
Abstract
The
geothermal
resources
in
hot
dry
rock
(HDR)
are
considered
the
future
trend
energy
extraction
due
to
their
abundant
reserves.
However,
exploitation
of
is
fraught
with
complexity
and
technical
challenges
arising
from
unique
characteristics
high
temperature,
strength,
low
permeability.
With
continuous
advancement
artificial
intelligence
(AI)
technology,
intelligent
algorithms
such
as
machine
learning
evolutionary
gradually
replacing
or
assisting
traditional
research
methods,
providing
new
solutions
for
HDR
resource
exploitation.
This
study
first
provides
an
overview
technologies
AI
methods.
Then,
latest
progress
systematically
reviewed
applications
reservoir
characterization,
deep
drilling,
heat
production,
operational
parameter
optimization.
Additionally,
this
discusses
potential
limitations
methods
highlights
corresponding
opportunities
AI's
application.
Notably,
proposes
framework
system,
offering
a
valuable
reference
practice.
Язык: Английский