Integration of borehole and airborne transient electromagnetic data for automatic compilation of ...

173 Pages·2014·13.72 MB·English

Integration of borehole and airborne
transient electromagnetic data for
automatic compilation of large scale
hydrogeological models

PhD thesis
by

Nikolaj Foged

Department of Geoscience
Faculty of Science and Technology
Aarhus University, Denmark
April 2014

Preface
This dissertation is submitted to the Graduate School of Science and Technology
(GSST), Aarhus University to be evaluated for a PhD degree in Geophysics.
The PhD candidate has not formal been registered at GSST, but scheduled scientific
research work and a Phd plan, was pre-approve in 2011 by GSST (at present time
AGSoS). The dissertation is therefore hand in under §15.2, “PhD dissertation for
assessment without a completed PhD programme” in the PhD order.
The main part of the thesis is related to research work carried out with in the last 2-3
years where the candidates work has been carried out in two research projects, with a
workflow close to a normal PhD student. The thesis also holds selected research work
carried out in the 12 years of employment as academic staff (AC-TAP) at the
Department of Geoscience, Aarhus University in the HydroGeophysics Group (HGG).
The bulk of the thesis consists of five papers, where at present stage two are
published, and three are submitted, all in internationally peer-reviewed journals. The
five papers are included in the appendices, and extended summary and discussion of
each paper are placed in chapters 5-9.
Main supervisor: Co-supervisor:
Professor MSO, Esben Auken Ass. professor, Anders V. Christiansen
Departmen of Geoscience, Department of Geoscience,
Aarhus University Aarhus University

Papers in peer-reviewed journals:
Included in this thesis
I Christiansen, A. V., N. Foged and E. Auken, A concept for calculating accumulated clay
thickness from borehole lithological logs and resistivity models for nitrate vulnerability
assessment, reviewed and re-submitted to Journal of Applied Geophysics, April, 2014.
II Foged, N., P. A. Marker, A.V. Christansen, P. Bauer-Gottwein, F. Jørgensen, A. Høyer, E.
Auken, Large scale 3D-modeling by integration of resistivity and borehole data through
inversion, submitted to HESS, January, 2014.
III Høyer, A.-S., F. Jørgensen, N. Foged, X. He, and A. V. Christiansen, 2014, Three-
dimensional geological modelling of AEM resistivity data - a comparison of two automatic
modelling concepts with manual cognitive modelling, submitted to Environmental
Modelling & Software, April, 2014.
IV Auken, E., A.V. Christiansen, J. A. Westergaard, C. Kirkegaard, N. Foged, and A. Viezzoli,
2009, An integrated processing scheme for high-resolution airborne electromagnetic
surveys, the SkyTEM system, Exploration Geophysics, 40, 184-192.
V Foged, N., E. Auken, A. V. Christiansen, and K. I. Sørensen, 2013, Test site calibration
and validation of airborne and ground based TEM systems, Geophysics, 78, E95-E106.
Co-author publications not included in this thesis
• Meier, P., T. Kalscheuer, J. E. Podgorski, A. Green, S. Greenhalgh, L. Rabenstein, J.
Doetsch, W. Kinzelbach, E. Auken, P. Mikkelsen, N. Foged, B. Jaba, G. Tshoso, and O.
I
Ntibinyane, 2014, Hydrogeophysical investigations in the western and northern Okavango
Delta (Botswana) using electrical resistance tomography (ERT) and transient
electromagnetic (TEM) techniques, Submitted to Geophysics 2014.
• Auken, E., A. V. Christiansen, C. Kirkegaard, G. Fiandaca, C. Schamper, A. A.
Behroozmand, A. Binley, E. Nielsen, F. Effersø, N. B. Christensen, K. I. Sørensen, N.
Foged, and G. Vignoli, An overview of a highly versatile forward and stable inverse
algorithm for airborne, ground-based and borehole electric and electromagnetic data,
Submitted to Exploration Geophysics 2013.
• Kirkegaard, C., N. Foged, E. Auken, A. V. Christiansen, and K. I. Sørensen, 2012, On the
value of including x-component data in 1D modeling of electromagnetic data from
helicopterborne time domain systems in horizontally layered environments, Journal of
Applied Geophysics, 84, 64-69.
• Pfaffhuber, A. A., E. Grimstad, U. Domaas, E. Auken, N. Foged, and M. Halkjaer, 2010,
Airborne EM mapping of rockslides and tunneling hazards, Leading Edge, 29, 956-959.
• Christiansen, A. V., E. Auken, N. Foged, and K. I. Sørensen, 2007, Mutually and laterally
constrained inversion of CVES and TEM data - A case study, Near Surface Geophysics, 5,
115-124.
• Auken, E., A. V. Christiansen, B. H. Jacobsen, N. Foged, and K. I. Sørensen, 2005,
Piecewise 1D Laterally Constrained Inversion of resistivity data, Geophysical Prospecting,
53, 497-506.
Selected 1st author peer-reviewed abstracts, presented at the confernces:
• Foged, N., A. V. Christiansen, and P. A. Marker, 2013, Large-scale automatic generation of
hydrological input from resistivities and boreholes, SAGA AEM, South Africa.
• Foged, N., E. Auken, P. Nehlig, J. Deparis, and J. Perrin, 2011, Geological Mapping using
Airborne TEM at Mayotte, 17th European Meeting of Environmental and Engineering
Geophysics, Leicester.
• Foged, N., A. V. Christiansen, and E. Auken, 2010, Validating SkyTEM Data Against
Ground-based TEM Data at the Danish National Test Site by Upward Continuation, EAGE
Zurich.
Acknowledgments
First of all I would like to thank my supervisor Esben Auken for offering me the
opportunity to obtain the PhD degree, for the supervision, and for providing the
funding for the PhD project in connection with the STAIR3D-project (funded by Geo-
Center Danmark) and the HyGEM-project (funded by the Danish Council for Strategic
Research under contract no. DSF 11-116763). I also wish to thank my co-supervisor
and colleague Anders V. Christiansen for dedicated teamwork and interaction in the
daily research progress. I also wish to emphasize the excellent cooperation with our
external partners and co-authors of the publications: Flemming Jørgensen and Anne-
Sophie Høyer (GEUS), Pernille Marker and Peter Bauer-Gottwein (DTU). Finally, I
sincerely thank my colleagues in the HydroGeophysics Group at Aarhus University,
who all, on different levels, have been involved in the research and development
carried out within my PhD project.

Nikolaj Foged, April 2014
II
Table of contents

Summary ...................................................................................................................... 1
Summary (Danish) ......................................................................................................... 3
1 Introduction ............................................................................................................ 5
2 Resistivity based petrophysical relationships ........................................................... 7
3 Geological modeling approaches ........................................................................... 13
3.1 Resolution, scale, and uncertainty issues ................................................................................... 13
3.2 Modeling approaches ................................................................................................................. 14
4 Hydrogeophysical mapping – geophysical resistivity methods ................................ 17
4.1 Data accuracy and calibration .................................................................................................... 17
4.2 Airborne EM systems .................................................................................................................. 18
4.3 Ground based systems................................................................................................................ 20
5 Estimating accumulated clay thickness from borehole and
resistivity data (paper I) ........................................................................................ 23
5.1 Introduction ................................................................................................................................ 23
5.2 Methodology .............................................................................................................................. 23
5.3 Hadsten field case - results ......................................................................................................... 27
5.4 Discussion ................................................................................................................................... 30
6 Large scale 3D-modeling by integration of resistivity models and
borehole data through inversion (paper II) ............................................................ 31
6.1 Methodology .............................................................................................................................. 31
6.2 Results - Norsminde field case .................................................................................................... 33
6.3 Discussion and outlook ............................................................................................................... 36
7 3D geological modeling of AEM resistivity data - a comparison of
modeling concepts (paper III) ................................................................................ 39
7.1 Modelling approaches ................................................................................................................ 39
7.2 Model comparison and discussion ............................................................................................. 41
7.3 Conclusion .................................................................................................................................. 43
8 Processing of SkyTEM data (paper IV) .................................................................... 45
8.1 Introduction ................................................................................................................................ 45
8.2 Methodology .............................................................................................................................. 45

III
9 Test site calibration and validation of Airborne and
ground-based TEM (Paper V) ................................................................................. 49
9.1 The Danish TEM test site ............................................................................................................. 49
9.2 Test site calibration ..................................................................................................................... 52
9.3 Validation of the SkyTEM-system................................................................................................ 54
9.4 Conclusion ................................................................................................................................... 57
10 Discussion and outlook .......................................................................................... 59
References ................................................................................................................... 63
Appendix 1
Paper I: A concept for calculating accumulated clay thickness from borehole
lithological logs and resistivity models for nitrate vulnerability assessment
Appendix 2
Paper II: Large scale 3D-modeling by integration of resistivity and
borehole data through inversion
Appendix 3
Paper III: Three-dimensional geological modelling of AEM resistivity
data - a comparison of two automatic modelling concepts with manual cognitive
modelling
Appendix 4
Paper IV: An integrated processing scheme for high-resolution
airborne electromagnetic surveys, the SkyTEM system
Appendix 5
Paper V: Test site calibration and validation of airborne and
ground based TEM systems
IV
Summary
Increasingly airborne electromagnetic methods are being used to provide large scale
and high quality surveys of the upper 300 m of the geological layers. The surveys
reveal a detailed and often complex picture of the resistivity distribution of the
subsurface. This information is useful when compiling geological and hydrogeological
models, since the formation resistivity correlates both to lithology and to hydrological
properties, and because borehole data have a low spatial density compared to airborne
surveys. To utilize the resistivity surveys in hydrogeological modeling, correlations to
geological or hydrological parameters need to be established. These correlations most
often need to be site specific to perform a valid and optimum interpretation of the
resistivity results. Traditional “manual” geological modeling can be very time
consuming when incorporating large scale dense geophysical surveys because of the
huge amount of data/information to integrate. Automatic or semi-automatically
integrated modeling utilizing both borehole and geophysical resistivity data therefore
seems a natural step to take to produce hydrogeological models in a relatively fast and
objective way.
In this PhD-project a concept has been developed for integration of resistivity and
borehole data to set up the structure of large scale hydrogeological models. This
concept is automatic and by inversion we determine the optimum translation of the
resistivity models into percentage of clay content. The inverse problem determines the
parameters of a translator function that gives the best fit between the clay content
described in the boreholes and the clay content computed from the resistivity models.
A key part in the concept is that the resistivity-to-clay translator function is
distributed (it varies in space), thereby taking variation in pore water resistivity, clay
mineral content and scaling issues into account in the translation. The concept has
been used for various applications. One application is to estimate the accumulative
clay thickness of clay layers overlying aquifers. This application is for vulnerability
assessment of aquifers. Another application of the modeling concept is an automatic
compilation of large scale 3D models, expressing the clay fraction of each voxel in a
3D-model. The 3D clay fraction model can easily be converted to a lithological sand-
clay model, incorporating the key information from both the borehole and the
resistivity dataset. One of the initial objectives of the integrated modeling concept was
to use it to set up large scale hydrogeological models to inform a groundwater model.
We have achieved this by making a clustering of the 3D clay fraction model, to form
hydrostratigraphic units for the hydrological model.
Another part of the PhD work was focused on the importance of high initial data
accuracy for the geophysical TEM measurements, where careful data processing, test-
site calibration and validation of the instruments are key elements to achieve this. A
comprehensive processing scheme for airborne TEM data has been further developed
as well as standardized focusing on processing of airborne TEM data from the
SkyTEM-system. The developed test-site calibration schemes for airborne and ground
based TEM instruments are based on calibration to reference responses. Since the
calibration is performed in data space, we obtain a very accurate set of calibration
parameters for each instrument. The comprehensive validation of the SkyTEM-system
confirmed a high initial data quality and a high quality in the subsequent processing
and inversion of the SkyTEM-data.
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Summary (Danish)
Storskalakortlægninger med luftbårne elektromagnetiske metoder (AEM) anvendes i
stigende grad i den hydrogeologiske kortlægning. De fladedækkende AEM
kortlægninger resulterer i en detaljerede 3D-resistivitetsmodel af de ofte komplekse
geologiske strukturer i undergrunden. Denne information er særdeles nyttig i
udarbejdelsen af geologiske og hydrogeologiske modeller, dels fordi resistiviteten kan
korreleres til litologiske og hydrologiske parametre, dels fordi boringstætheden
normalt er for lille til at repræsentere den geologiske kompleksitet. For at anvende
resistivitetskortlægningerne i den hydrogeologiske modellering, skal resistivitets-
værdierne korreleres til geologiske og/eller hydrologiske parametre. Integrering og
tolkning af storskala AEM resistivitetskortlægninger i en traditionel manuel geologisk
modelleringsproces er meget tidskrævende. Endvidere er en traditionel ”manuel”
geologisk modelleringsproces relativt subjektiv i tolkningen af de geofysiske
resultater. Automatiske og semi-automatiske modelleringskoncepter, der integrerer
boringsinformation og geofysiske kortlægninger, kan levere et målrettet input til en
grundvandsmodel på en relativt hurtig og objektiv måde.
I PhD-projekt er der udviklet et modelleringskoncept, der integrerer de geofysiske
resistivitetsmodeller og boringer i udarbejdelsen af 3D hydrogeologiske modeller.
Konceptet er automatisk og bygger på en lokal oversætter af resistivitetsværdierne til
et ler-indhold. Ved inversion bestemmes den mest optimale resistivitet til ler
oversætterfunktion. En central del af konceptet er, at oversætterfunktionen kan
variere rummeligt, således at den resulterende ler-fraktionsmodel er i
overensstemmelse med både de geofysiske modeller og boringerne. Konceptet har
forskellige anvendelsesområder. Således er konceptet blevet anvendt til estimering af
den akkumulerende lertykkelse til sårbarhedsvurderinger af grundvandsmagasinerne.
En anden anvendelse af det automatiske modelleringskoncept er til generering af
storskala 3D- lerfraktionsmodeller eller litologiske ler-sand modeller. Et af de
oprindelige formål med modellerings-konceptet var automatisk, at kunne generere
storskala hydrogeologiske modeller indeholdende hydrostratigrafiske enheder til en
grundvandsmodel. Dette er opnået ved at lave en clustering af ler-frationsmodeller.
En 3D-model med hydrostratigrafiske enheder er blevet udarbejdet for Norsminde
testområdet, og en grundvandsmodelkalibrering af modellen er udført med foreløbige
positive resultater til følge.
I PhD-forløbet er der også blevet arbejdet med processering, kalibrering og validering
af TEM-data og TEM-instrumenter. Dette har bl.a. medført videreudvikling og
standardisering af de forskellige processeringsrutiner for AEM-data. Endvidere er der
udviklet en kalibreringsprocedure for jordbaserede og luftbårne TEM-instrumenter,
der bygger på kalibrering til referencerespons for teststed. Da kalibreringen foretages
i data-domænet, opnår vi en meget præcis kalibrering af TEM- instrumenterne. Den
udførte validering af SkyTEM-systemet (AEM metode) på baggrund af målinger på
teststedet, bekræftede en høj datakvalitet for SkyTEM systemet og en høj kvalitet i
den efterfølgende processering og inversion af data.

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