►
From YouTube: SimPEG Meeting from January 5th
Description
SimPEG weekly meeting from January 5th, 2022
A
A
Like
things
we'd
like
to
see
added
things,
we'd
want
areas
that
we
kind
of
want
to
focus
on
just
looking
forward
to
the
new
year
to
see
where
people
are
at
what
they're,
what
they're
hoping
to
do
with
zimbag
it'd
be
nice
to
kind
of,
like
you
know,
take
this
role
and
kind
of
focus.
Us
focus
see
what
we're
interested
in.
Obviously
it's
you
know
what
people
want
to
tackle
they're
going
to
tackle
that
just
to
have
an
idea
of
where
people
are,
though,
so,
just
kind
of
start.
A
Thinking
about
that,
I'm
assuming
we
don't
have
too
many
quick
reports
over
the
last
two
weeks
myself.
I
I
you
know
spent
the
last
few
weeks
with
family
down
in
the
states.
I
don't
think
we
caught
covet
because
we
were
let
back
into
canada
yesterday.
So
it's
all
good,
though
I
have
an
article
going
through
with
the
copy
editing
status
for
geophysics
that
should
be
coming
out
soon,
so.
A
A
Yeah,
it
is
on
like
combining
gravity
and
gravity
radiometry
data,
just
a
little
bit
more
rigorous
than
it's
actually
most
almost
every
other
piece
of
work
that
has
ever
been
published
about
is
more
rigorous
of
an
approach
to
it
about
how
how
to
adequately
combine
them.
Thought
processes
just
kind
of
a
general
steps
you
should
take
when
you
want
to
combine
them
and
why
and
what
they
can
do
together.
A
A
I
say
it
was
my
mini
masters
project
that
I
did
within
within
my
phd,
like
it
had
nothing
to
do
with
any
of
my
phd
topics
and
just
like.
Essentially
it
would
have
been
a
master's
project
on
its
own,
but
it
was
just
a
neat
fun
little
thing
to
do
off
to
the
side,
so
that'll
be
hopefully
coming
out
in
geophysics
soon,
and
I
should
be
able
to
share
it
shortly.
A
A
It's
one
of
the
things
where
it's
like,
I
don't
it's
about
like
we
do
have
to
actually
properly
weight
the
two
different
types
of
data
sets,
or
else
they
just
don't
fit.
They
don't
fit
and
you
don't
you
kind
of
lose
out
on
the
benefits
of
combining
them.
If
you
don't
properly
weight,
each
of
them
individually,.
D
A
B
Quickly,
I'm
sure
most
people
saw
this
here,
but
I'll
just
point
it
out.
If
you
know
anybody
who's
interested
in
a
postdoc
looking
at
em
for
uxo,
primarily
so
both
sort
of
combining
inversion
as
well
as
machine
learning.
Please
put
them
in
touch
so,
but
yeah,
em
kind
of
being
the
biggest
thing.
If
they've
never
worked
with
uxo,
that's
fine,
but
if
they
worked
with
em
or
neural
networks.
That
would
be.
That
would
be
great.
C
B
D
B
D
B
D
A
C
Reports
yeah,
maybe
I
have
what
I
wrote.
I
I
it
was
pure
accidents
when
I
stumbled
on
this
art
read
the
docs
link
and
I
thought
even
it
took
me
a
while
to
realize
that's,
that's
very
old
documentation
and
I
know
simpex.
I
thought
if,
if
another
user
stumbles
up
in
these
old
documentation,
it
might
be
bad.
So
I
don't
know
who
has
the
login
credentials
for
read
the
docs
if
that
can
just
be
removed
or
if
you
have
to
update
something
or.
D
C
D
E
C
B
B
A
A
B
C
B
C
C
B
Things
pointing
at
the
same
url
because
read
the
docs
right
now,
you're
right,
we
are
pointing
to
the
simpeg.xyz
site
and
we're
doing
that
with
github,
and
so
the
fact
that
you
have
the
slash
en
slash
latest
grabs
read
the
docs,
whereas
the
other
one
grabs.
If
you
leave
that
off
we'll
grab
github.
So
that's
super
confusing.
A
D
Now,
I'm
kind
of
working
down
the
unit
test
to
make
sure
they're
still
passing
and
then
adding,
like
you
know,
duplication,
duplication,
warnings
for
all
the
name
changes
I
think,
there's
like
so
much
stuff
in
there
that
we
should
probably
have
like
a
quick
overview
together
for
people
who
want
to
do
a
review,
because
it's
obviously
a
you
know,
it's
a
big
module,
the
regularization.
So
we
should
probably
agree
on
changes,
agree
or
disagree
on
changes.
D
A
D
D
I
re-ran
it
and
if
numpy
is,
if
I
pin
mkl
to
like
the
the
right
version
that
works
but
numpy
is,
is
ahead:
it's
like
the
latest,
then
it
still
doesn't
work.
So
it
needs
to
be
numpy
a
specific
version
and
then
pi
mkhill
specific
version.
I'm
guessing
we're
using
numpy
to
compile
the
c
code
right
still
so.
D
C
C
A
E
I
mean
I
don't
have
anything
else,
that's
too
much.
Simpag
related,
but
lately
I've
been
working
on
a
lot
of
utem
data,
so
this
is
like
a
large
inductive
loop
source
and
the
idea
is
you've,
got
sort
of
a
triangular
waveform
and
you're
measuring
db
dt,
but
it's
equivalent
to
measuring
the
b
field
for
a
step.
E
So
this
is
it's
kind
of
an
interesting
setup
because
to
invert
these
data,
you
have
basically
data
collected
during
the
on
time
and
so
looking
ahead.
There's
you
know
some.
I
don't
think,
there's
a
well-established
strategy
for
inverting
those
those
data
and-
and
you
know,
dealing
with
kind
of
the
same
issues
we
have
when
we
do
frequency
domain
em,
where
we
have
to
account
for
a
primary
field.
So
it's
kind
of
a
fun
project.
C
My
pinterest
a
lot
of
the
few
stuff
that
was
done
time
domain
in
marine
cscm
is
usually
done
the
same.
So
it's
a
continuous
source
signal,
but
it's
not
a
wave.
So
it
it
it's
it's
a
it's
a
more
complicated
source
signal
and
it's
then
pinned
and
then
done
into
time
windows
and
used
as
time
domain
data.
But
it's
also
measured
well,
there's
not
an
on
and
off
time,
it's
always
on
and
you
measure
at
the
same
time.
So
there
might
be
similar
strategies
to
use.
E
G
G
E
When
you
represent
the
data
you
normalize
by
by
the
primary
field,
essentially
to
try
and
see
what
kind
of
anomalous
structures
are
there,
so
I'm
not
sure
if
there
is
a
a
standard.
You
know
I've
only
really
played
with
this
one
data
set,
but
I
have
been
given
effectively
this
total
field
day.
I've
just
been
given
what
was
measured
by
the
receivers,
and
it
includes
the
primary.
E
E
E
E
Well,
I
haven't
seen
inversion
results
for
this
yet,
and
I
know
scott
napier
had
a
masters
or
a
phd
thesis
in
like
over
a
decade
ago.
They
played
around
with
this
system,
but
he
inverted
the
the
total
field
like
he
inverted
all
of
it,
and
I
mean
a
lot
of
what
we're
doing
right
now
and
what
the
sponsors
are
interested
in
is
what
is
the
best
approach,
so
I'm
definitely
gonna
try
a
few
things
they
want.
They
want
a
consistent
strategy
for
this
type
of
data.
F
I
did
a
project
like
this
with
the
old
company
that
I
worked
with.
We
were
doing
downhole,
step
response
and
yeah
soggy.
That's
exactly
what
you
do
is
you
remove
the
primary
and
then
they
would
just
put
it
into
maxwell
and
they
would
just
model
plates
with
the
on
time.
There
wasn't
an
inversion
at
the
time,
but
yeah
you
removed
the
primary
for
sure.
F
E
Yeah,
I
don't
know
exactly
what
they're
working
with,
but
you
just
basically,
if
you
are
modeling
the
total
field
for
in
with
using
these
codes,
the
new
the
errors
associated
with
numerically
modeling.
The
primary
field
are
larger
than
the
uncertainties
on
your
data
and
that
that
buggers
everything
so
always
wanting
to
try
to
invert
anomalous
and
not
total
field.
That
so
far,
that's
that's
my
my
feeling,
unless
somebody
can
convince
me
otherwise,
but
I
think.
G
It's
very
worthwhile
to
kind
of
read
a
little
bit
more
because,
like
then,
and
to
me
like,
what's
the
point
actually
like
a
measuring
on
time,
data
like
like
a
time
the
beauty
of
the
time
domain,
I
think,
can
actually
measure
the
out
of
time
without
the
primary
field.
I
think
so.
I
think
that
there
should
be
there's
some
physical
reason
why
they
are
doing
it
and
yeah
actually
understanding.
That
would
be
actually
quite
nice.
E
C
E
G
G
So
if
you
got
very
late
time
gates
that
you
want
to
measure
a
signal
just
using
the
voltage,
it'll
really
suffer
from
kind
of
having
that
very
like
a
late
time
signals,
whereas
the
b
field
it
seems
like
that
was
my
understanding
in
general,
like
you,
can
have
lower
frequency
band
by
using
the
b
field,
but
here
by
kind
of
like
by
manipulating
the
waveform
you're
getting
the
b
field.
But
is
it
really
helps?
E
E
E
G
Nothing
particular
I
was
completely
off
completely
playing
with
my
son.
I,
before
the
break,
I
made
some
improvements
in
the
the
1d
code,
so
now
I'm
actually
pretty
happy
with
the
the
current
version,
so
it's
actually
now
optimized
so
and
it's
actually
quite
faster
than
I'm
not
sure.
I
haven't
really
checked
the
one
two
one
I
think
it's
couple
times
faster
and
the
memory
issue
like
I
had
a
bit
of
memory
issue
with
the
new
version
I
fixed
it.
G
G
So
one
example
that
I'm
currently
working
on
is
the
the
sea
water
intrusion
at
the
coastal
airborne
data
at
quite
a
coaster
area,
so
yeah,
it's
all
three
large
like
a
typical
size
of
about
a
thousand
micrometer,
and
it
takes
about
like
a
couple
of
hours
to
run
with
like
10
quarts
or
something
like
that
and
yeah.
So
I'm
like.
So
this
is
actually
what
was
my
first
time
using
the
new
code
for
sort
of
the
field
scale.
A
large
scale
am
version
and
it
seems
like
working
quite
well.
G
At
least
like
gives
sort
of
the
same
result
that
I
have
used
before.
So
I'm
pretty
happy
and
yeah.
This
is
kind
of
like
a
typical
way.
The
steps
that
I
do
I
invert
for
smooth
and
use
the
different
reference
model.
You
can
see
pretty
big
differences.
The
bread
is
the
big
conductor,
the
intruder
sea
water.
But
this
part
we
got
very
low
confidence,
as
you
can
see,
because
I
use
the
like
a
0.3
as
a
reference
or
I
can
use
like
20
ohm
meter,
for
instance,
freshwater
resistivity
as
a
reference.
G
Data
like
my
many
times
like
a
10
time
lapse
data.
I
have
10
models
that
I
want
to
connect
through,
but
I
may
connect
for
each
two
of
them
so
yeah.
I
could
wait
on
myself,
but
this
is
something
that
I
need.
So
if
there
is
an
existing
sort
of
the
base
class,
I
wanted
to
use
anyway.
So
you
want
you
want
to.
A
G
It's
it's
the
same
physical
property,
but
set
it
as
a
different
model
because,
like
it's,
a
resistivity
at
2017
and
resistivity
in
2019..
So
although
it's
the
same
physical
property,
it's
it's
different
because,
like
there's
a
time
time
component-
and
I
think
it's
potentially
what
we
can
develop
as
a
general
like
a
class
like
a
time-lapse
regularization
class,
because
I
think
the
need
is
kind
of
like
a
getting
more
and
more
because,
like
ert,
for
instance,
there
are
many
time
lapse.
G
Data
like
a
co2
injection,
the
types
of
monitoring
issues
so
having
something
simple
like
basically
putting
the
the
flatness
or
the
smoothness
in
time
direction,
so
that
in
the
easiest
case,
if
the
mesh
is
exactly
the
same,
we
can
literally
put
the.
I
think
you
can
just
use
the
existing
kind
of
mesh
structure
to
put
the
time
constraint.
But
sometimes
the
mesh
can
be
different.
That
is
the
case
for
me.
G
D
A
D
A
G
Yeah
yeah
yeah,
so
I
can
just
slack
stack
over
a
whole
bunch
of
regularization.
Well,
in
this
case,
I
just
only
need
two
only
one
linkage,
but
we've
got
many
times
we
can
just
stack
over.
So
I
thought
that's
that's
an
okay
way
to
deal
with
that.
So
so
joe,
there
is
a
base
class
for
that
that
I
can
use.
C
A
G
Perfect
yeah
and
that
that
is
a
project
that
I'm
kind
of
working
for
the
next
three
months
and
we're
basically
constraining
the
the
hydrologic
modeling,
the
smaller
intrusion
modeling
using
the
airborne
em
data.
So
the
other
item
that
I
am
going
to
update
is
the
3d
airborne
em
simulation.
So
I
kind
of
wrote
the
the
local
mesh
idea
very
specific,
very
specific
example
for
skytem
system,
but
I'm
hoping
to
either
bring
in
or
at
least
update,
that
that
to
be
compatible
with
the
existing.
G
G
C
G
G
G
A
A
G
G
So
this
was
actually
the
top
that
I
gave
in
agu
and
this
is
the
inside
data.
So
if
this
threat
is
the
big
subsidence
for
five
years,
so
it's
about
like
a
meter
for
five
years,
which
is
crazy.
So
if
you
think
about
the
infrastructure
like
a
train
having
a
one
meter
substance,
it
can
kind
of
destroy
when
there's
a
canals
going
on.
So
it's
actually
a
big
risk.
G
A
whole
bunch
of
insert
signals
and
take
the
mean
it's
a
kind
of
it's
a
proof
of
concept,
so
I
just
take
the
mean
value
and
then
I
got
like
you
do
need
to
know
the
subsurface
properties
about
the
clays
and
what
is
the
storage
coefficients
and
stuff
like
that?
So
I
assume
that
I
can
get
invert
like
I
get
that
information
from
other
literature.
So
I
fixed
that.
Then
this
is
the
data
in
star
data
and
the
goal
is
getting
recovering
the.
G
G
Function
is
the
the
changes
in
head
is
the
model.
The
data
is
the
that
subsurface
information
and
that's
what
I
was
able
to
recover.
So
I
fit
the
data
and
that
this
part
is
actually
important.
The
data
is
not
only
affected
by
this
point,
but
the
historical
have
changes
actually
affecting
the
data
in
future.
So
somehow
you
estimate
this,
but
you
need
the
good
rate,
the
linear
rate,
but
once
you
got
okay
rate,
I
was
able
to
fit
the
data
well
and
here's
my
pitch.
G
So
if
you
actually
compare
with
the
the
the
the
actually
measured
data
close
by
and
that's
what
you
get
so
this
is
the
actually
measured
head
and
how
the
measured
head
is
changing
and
this
threat
is
where
you
got
the
drug
period.
So
if
you
think
about
the
drug
period,
had
this
going
down,
so
that's
the
problem
like
for
groundwater
and
management
head
is
going
that
water,
water
level
going
down
is
a
problem
in
general
and
after
the
drop
it
kind
of
slowly
recovers
and
oscillate,
you
can
see
kind
of
the
good
trend.
G
Goes
up
goes
up,
goes
down,
goes
up
and
the
the
the
measured
data
only
have
a
sparse
point,
whereas
the
measured
instar
data
have
like
a
much
better
time
sampling.
So
the
recovered
the
recovered
head
that
we
can
get
has
a
much
better
temporal
resolution
and
what
will
be
really
cool
is
expanding
that
into
the
entire
central
valley
like
here.
G
So
then
you
can
actually
monitor
the
head
changes
in
the
entire
central
valley
with
the
high
spatial
resolution,
which
will
be
absolutely
challenging
yet
because
there
are
other
challenges
remaining
challenges,
but
I
was
relatively
happy
with
what
we
were
able
to
get
and
the
implementation
wasn't
wasn't
too
hard
with
the
existing
syntax
structure
and
this
especially
for
desperate
eyes.
So
anyway,.
D
G
D
G
D
G
G
History-
it's
not
just
one
year
ago,
it's
like
tens
of
like
hundreds
of
years
so
but
that
impact
is
getting
reduced
as
you
as
time
goes
by
and
then
the
inverted
process
likely
can
find
an
effective,
effective
like
a
time
history
in
a
way,
and
then
there
are
many
wells
so
not
only
like
I
it's.
We
have
some
data
that
I
can
interpolate
over
there
that
I
can
start
from
so
in
the
end,
we're
going
to
invert
all
of
them
together.