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Incorporation of Magnetic Resonance Sounding data into groundwater models through coupled and joint inversion. 8th Annual Meeting of DWRIP 2014 JANUARY 30 T.N . Vilhelmsen, A.A . Behroozmand, S. Christensen, E . Auken, and A.V . Christiansen. Outline.

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Presentation Transcript
slide1

Incorporation of Magnetic Resonance Soundingdata intogroundwater models through coupled and joint inversion

8th Annual Meeting of DWRIP

2014 JANUARY 30

T.N. Vilhelmsen, A.A. Behroozmand, S. Christensen,

E. Auken, and A.V. Christiansen

outline
Outline
  • Coupled vs. Joint inversion (MRS and groundwater model)
  • Mapping the groundwatertableusing MRS
  • Results from coupled inversion tests (synthetic model)
  • Perspectives for 3d joint inversion
joint vs coupled inversion
Joint vs. coupled inversion

Joint inversion

  • Inversion setup is linked through shared parameter characteristics
  • Here: Transmissivity derived from MRS (using petrophysical relation) is linked to transmissivity in a hydrological model (through regularization)

Coupled inversion

  • Tight link directly through model forward responses
  • Here: Groundwater flow model is used to simulate the thickness of the upper layer in an MRS model (unsaturated zone)
coupled inversion using mrs
Coupled inversion using MRS

MRS model:

Simulated by groundwater model

Layer 1

w,T2*,lt.

Layer 2

w,T2*,lt.

Layer 3

w,T2*,lt.

slide5

The test model

  • Two aquifers separated by an aquitard
  • Two recharge zones
  • Well pumping from lower aquifer
  • Flow in from adjoining hill side
  • Flow out through river
  • Model observations generated using heterogeneous parameter fields

After: Hill, et al., 2000

slide6

Reference model (50 realiazations):

  • Heterogeneous k-fields (calculated from water content and decay time fields)
  • 10 head obs.
  • 1 river discharge obs.
  • 1 MRS sounding (located at prediction point)
the inversion setup
The inversion setup:

PEST

  • Groundwater model parameter files:
  • Hydraulic conductivity zones
  • River bed conductance
  • Recharge
  • Groundwater model
  • (MODFLOW-2005)
  • Simulated heads
  • Simulated river flow

Thickness of unsat. zone

  • Geophysical model parameter files:
  • Holds all geo. phys. par. Except for layer 1 thick (unsaturated zone)
  • Geophysical model
  • (AarhusInv)
  • Simulated MRS resp.
  • Simulated TEM resp.
inversion results 50 models
Inversion results (50 models)

Goal: Achieve the most accurateprediction of head at MRS location

  • Error variance similar / mean error larger
  • Independent geophysical inversion cannot improve groundwater model prediction
3d joint inversion of mrs and groundwater models
3d joint inversion of MRS and groundwater models
  • Goal:
  • Use MRS to improve estimate of hydraulic conductivity heterogeneity in groundwater flow models
  • Estimate parameters pertaining to the petrophysical relation together with MRS/TEM and hydrological parameters using a regularized coupling
the joint inversion methodology
The joint inversion methodology

PEST

Hydrological

data

Hydrological

parameters

Hydrological

simulation

Groundwater model

Geophysical

simulation

Geophysical

data

Geophysical

parameters

Geophysical model

the joint inversion methodology1
The joint inversion methodology

PEST

Hydrological

data

Hydrological

parameters

Hydrological

simulation

Groundwater model

Petrophysical

relation

Geophysical

simulation

Geophysical

data

Geophysical

parameters

Geophysical model

Petrophysical relation:

Tmrs= [Cp * wa * (T2*)2]*lt

Regul. Obj. Fun.

ristrup well field1
Ristrup well field

MRS sounding

ristrup well field2
Ristrup well field

MRS sounding

perspectives and conclusions
Perspectives and conclusions
  • Joint inversion
    • Expected to increase resolution of hydraulicconductivityinhomogeneity
    • Setup tested and works for a 2d case
    • Using joint inversion MRS canbelinked to several types of hydrological data (not onlyaquifer tests)
  • Coupled inversion
    • Canreduce head predictionerror
    • Will onlywork for unconfinedconditions
    • Will be most applicable in remoteareas with limited (hydrological) data coverage