K
laas H.
Scholt
and Mud Volcanism
and Mud Volcanism
in Azerbaijan
in Azerbaijan
HYPERSPECTRAL REMOTE SENSING
AND MUD VOLCANISM
IN AZERBAIJAN
HYPERSPECTRAL REMOTE SENSING
AND MUD VOLCANISM
IN AZERBAIJAN
Proefschrift
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus prof.dr.ir. J.T. Fokkema, voorzitter van het College van Promoties,
in het openbaar te verdedigen op dinsdag 28 juni 2005 om 10:30 uur
door Klaas Harm SCHOLTE
Doctorandus in de ruimtelijke wetenschappen geboren te Borne.
Prof. dr. S.B. Kroonenberg
Samenstelling promotiecommissie:
Rector Magnificus voorzitter
Prof. dr. F.D. van der Meer Technische Universiteit Delft, promotor Prof. dr. S.B. Kroonenberg Technische Universitiet Delft, promotor Prof. ir. C.P.J.W. van Kruijsdijk Technische Universiteit Delft
Prof. dr. S.M. De Jong Universiteit Utrecht
Prof. dr. I.S. Guliyev National Academy of Sciences, Azerbaijan Prof. dr. em. J. Thorez Université de Liège
Dr. R.F. Hanssen Technische Universiteit Delft
Published and distributed by PrintPartners Ipskamp B.V. ISBN-10: 9090196358
ISBN-13: 9789090196350
Copyright © 2005 by Klaas H. Scholte, Department of Geotechnology, Delft University of Technology
All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilised in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without the prior written permission by the author.
Printed in the Netherlands
Cover picture from Anke Dählmann, Utrecht University, Faculty of Earth Sciences, used with permission.
Acknowledgements
During the four and a half years I worked on this thesis, many people helped me in one way or the other. Therefore I would like to take the opportunity to thank all of them, their support has been crucial to me.
First, and most importantly, I want to thank my supervisors FREEK VAN DER MEER and SALLE KROONENBERG. The freedom and time you provided to let me find out the things myself has been a great thing for me. Freek, I really appreciated our Monday coffee breaks from 10 till 16, where we discussed all kinds of matters, not only related to the work of my PhD. Salle, your door was always open to direct my unstructured thoughts into ordered ideas and suggestions.
Secondly, I owe many special thanks to THOMAS KEMPER (DLR) and LAMMERT KOOISTRA (WUR). Your work on PLSR modelling helped me to brigde the gap between my field and image data, and your publications and theses have been very stimulating for me.
Doing fieldwork in Azerbaijan has been a great and wonderfull experience. However it is also physically and mentally demanding and only with the help and enthousiasm from a lot of people the data could be collected. The fantastic support from the Geological Institute of Azerbaijan, ELMIRA ALIYEVA and DADASH HUSEYNOV in particular, provided the logistical infrastructure for the field surveys. BOB HOOGENDOORN, JELLE BOELS, ANNEKE HOMMELS, and PETER KLOOSTERMAN(†) suffered long hot Azerbaijan sunny days to contribute to the selection of the field spectroscopic and subsurface data, and especially DAAN RIJKS for sacrificing his holidays for the scientific world!
During my stay at the Applied Geology section I was always very well received by all the collegues. In particular the nice and relaxed atmoshpere created by BOB, JOEP, LUC, REMCO, MARIT, ISRAEL, JOSE, ATA, GERT-JAN, JON, JELLE, IRINA, RICK, RORY, JAN-KEES and KEES contributed heavily to the perfect environment I need for doing research and writing a thesis.
I am indebted in particular to ANNEKE HOMMELS, EVERT SLOB, RAMON HANSSEN, and GINI KETELAAR for their constructive help and stimulating discussions on the geophysics (Anneke and Evert) and InSAR (Anneke, Ramon, and Gini) parts of this thesis.
ROB JORDANS and REMKO DE LANGE (MD-GAR); thanks for letting me use your ASD fieldspec in the field. I also thank ARMAND JONGEN and ABDELWAHEB AMARA (CREASO B.V.) for their support concerning the IDL programming.
Acknowledgements
There are many people I want to thank for their moral support and friendship (of similar importance as work related stuff): DAAN (danoaoao), BAS (henk), BAS (bop), DAAN (staay), LUCAS, HELEEN, JEROEN, REMKE, JURJEN, JURGEN, RIANNE, RENÉ, ARNO, MARIAN, DIEDERIK, EVELINE, WALTER, ALINDA, NIELS, KIM, EDITH, MARJOLEIN, KIM, SYLVIA, and all the soccer players from the HERCULES squades (indoor and outdoor) with whom I spent many enjoyable hours (not only on the pitch!).
PAP en MAM, your absolute support for all my ideas and stubbornness gave me the stamina to put the final parts of the thesis together: thanks!
Finally, my deepest love and gratitude goes to SONIA for being simply wonderful as you are!
ACKNOWLEDGEMENTS... i
TABLE OF CONTENTS... iii
LIST OF TABLES AND FIGURES... vi
LIST OF ACRONYMS ... viii
SUMMARY ... ix
SAMENVATTING... xii
1 GENERAL INTRODUCTION ... 1
1.1 Introduction to the problem... 1
1.2 Objectives and workflow of the study ... 2
1.3 Thesis organization ... 4
2 FIELD SITE ... 7
2.1 Regional geology ... 7
2.2 Mud volcanism ... 9
2.3 Geochemical processes ... 10
2.3.1 Ascending mineralogy along mud volcano chimneys... 10
2.3.2 Hydrocarbon-induced environment ... 11 2.4 Study sites ... 11 2.4.1 Aktharma-Pashaly... 13 2.4.2 Bakhar... 14 2.4.3 Bozdag-Kobijsky ... 15 2.4.4 Cheildag... 15
2.5 Mud volcano shallow subsurface... 16
2.5.1 Method... 16
2.5.2 Results Bozdag-Kobijsky ... 16
2.5.3 Results Lokbatan ... 17
2.5.4 Results Dashgil ... 17
2.6 Volcano activity from Interferometric SAR... 20
2.6.1 Introduction to Interferometric SAR... 20
2.6.2 Application-oriented analysis in a spatial context ... 21
2.6.3 Results ... 21
2.7 Summary... 22
3 MUD VOLCANO REFLECTANCE SPECTROSCOPY ... 25
3.1 Introduction to reflectance spectroscopy ... 25
3.2 Interaction of electromagnetic radiation with matter ... 25
3.2.1 The absorption process ... 26
3.3 Spectral properties of selected materials related to the study ... 27
3.3.1 Spectra of phyllosilicates ... 27
3.3.2 Spectra of organics... 27
3.3.3 Spectra of iron oxides, sulphides, and carbonates... 28
3.4 Interpretation of productive series ... 30
Table of contents
3.6.1 Visible hydrocarbon seepage...33
3.6.2 Invisible hydrocarbon seepage ...33
3.6.3 Fresh mud volcano flows...34
3.6.4 Old mud volcano flows ...34
3.6.5 Linking the shallow subsurface to reflectance spectroscopy parameters...35
3.7 Summary ...35
4 MAPPING OF MUD VOLCANO LITHOLOGY WITH VNIR AND GAMMA-RAY SPECTROSCOPY...37
4.1 Introduction ...37
4.2 Experimental...38
4.2.1 Mud volcanoes ...38
4.2.2 X-ray diffraction measurements ...38
4.2.3 Gammy-ray measurements...38
4.2.4 VNIR spectral measurements ...39
4.2.4.1 Spectral resampling ...39
4.2.4.2 Spectral pre-processing ...39
4.2.5 PLSR model construction and pre-processing...40
4.3 Results and discussion ...44
4.3.1 Interpretation of XRD analysis...44
4.3.2 Interpretation of natural radioactivity...46
4.3.3 Interpretation of VNIR spectra ...49
4.3.4 Prediction of natural radioactivity using PLSR ...50
4.4 Simple wavelength approach...55
4.5 Conclusions ...56
5 A MULTIPLE ENDMEMBER APPROACH FOR MAPPING MUD VOLCANO PRODUCTS USING ASTER DATA ...59
5.1 Introduction ...59
5.2 Data Set ...61
5.2.1 Sensor description ...61
5.2.2 Data set description ...62
5.2.3 ASTER data pre-processing ...62
5.2.3.1 Crosstalk...63
5.2.3.2 Co-registration...63
5.2.3.3 De-vegetation through forced-invariance...65
5.3 Methods: The Variable Multiple Endmember Approach ...65
5.3.1 Selection of key endmembers...66
5.3.2 Optimalization of the endmember-model...70
5.3.3 Standardized unmixing...71
5.4 Analysis of mud volcano composition...72
5.4.1 Aktharma-Pashaly ...72
5.4.1.1 Derivation of mud volcano products for the year 2001...72
5.4.1.2 Derivation of mud volcano products for the year 2002...77
5.4.3 Cheildag... 81
5.4.4 Bozdag-Kobijsky ... 85
5.4.5 Outcropping Productive Series at Kirmaky Valley... 87
5.5 Discussion... 89
5.6 Conclusions... 92
6 EO-1 HYPERION ANALYSIS FOR AKTHARMA-PASHALY MUD VOLCANO... 93
6.1 Introduction... 93
6.2 Data set and methods ... 94
6.2.1 Hyperion pre-processing... 94
6.2.1.1 Fixing bad pixels ... 94
6.2.1.2 Re-calibration ... 94
6.2.1.3 Spectral subsetting... 95
6.2.1.4 Fixing out of range data... 95
6.2.1.5 Data dimensionality and SNR... 95
6.2.1.6 Fixing outlier pixels... 95
6.2.1.7 De-smiling and de-streaking... 96
6.2.2 Atmospheric correction using ACORN ... 96
6.2.3 The Variable multiple endmember approach... 98
6.3 Results and discussion ... 98
6.3.1 Identification of endmembers ... 98
6.3.2 Comparative analysis for ASTER and Hyperion ... 103
6.4 Conclusions... 108
7 SYNTHESIS AND CONCLUSIONS ... 109
7.1 Introduction... 109
7.2 Mud volcano dynamics ... 109
7.3 Mud volcano compositional information ... 109
7.4 Methodological implications... 111 7.4.1 Quality of PLSR models ... 111 7.4.2 Image pre-processing... 112 7.4.3 Quality of unmixing... 112 7.5 General conclusions ... 113 REFERENCES ... 115 ANNEX ... 131 CURRICULUM VITAE ... 143 PUBLICATIONS ... 145
List of figures and tables
List of figures
Figure 1.1: Flowchart of the fundamental work steps... 4
Figure 1.2: Overview of available data. ... 5
Figure 2.1: General mineral provenance map. ... 8
Figure 2.2: General mud volcano cross sectional... 9
Figure 2.3: General geologic map and studied mud volcanoes of the investigated area... 12
Figure 2.4: overview of Aktharma-Pashaly summit ... 13
Figure 2.5: Bozdag-Kobijsky resistivity subsurface measurements... 17
Figure 2.6: Lokbatan subsurface resistivity.. ... 18
Figure 2.7: Dashgil resistvitiy subsurface measurements. ... 19
Figure 2.8: mud volcano dynamics using InSAR... 21
Figure 2.9: Mean deformation for seventeen mud volcanoes ... 23
Figure 3.1: Schematic diagram mineral absorption features ... 26
Figure 3.2: Reflectance spectra of phyllosilicates... 28
Figure 3.3: Reflectance spectra of montmorillonite and oil. ... 29
Figure 3.4: Reflectance spectra of hematite and goethite... 29
Figure 3.5: Reflectance spectra of pyrite, calcite and gypsum... 30
Figure 3.6: Schematic spectral stratigraphic column b ... 31
Figure 3.7: Reflectance spectra of Maykop Source Rocks... 32
Figure 3.8: Reflectance spectra of several mud volcanoes... 33
Figure 3.9: Relation between subsurface and diagnostic absorptions ... 35
Figure 4.1: Flowchard of the PLSR data arrangement ... 41
Figure 4.2: Box plots of natural radioactivity ... 47
Figure 4.3: Standard Normal Variate (SNV) and first derivative (right) spectra ... 49
Figure 4.4: F-ratio for natural radioactivity for different spectral pre-processing methods ... 51
Figure 4.5: PLSR coefficients for natural radioactivity exhibiting important wavelength regions... 53
Figure 4.6: Plots of the measured versus predicted natural radioactivity... 54
Figure 4.7: Overview of PLSR methodology using ASTER bandpasses... 57
Figure 5.1: Two dimensional spectral data ... 60
Figure 5.2: Overview of the ASTER ‘crosstalk’ correction... 64
Figure 5.3: ASTER devegetated imagery through forced invariance. ... 67
Figure 5.4: Flowchart of the VMESMA working scheme. ... 68
Figure 5.5: USGS mineral spectra resampled to ASTER... 70
Figure 5.6: Reflectance and standardized reflectance of Aktharma-Pashaly mud flows and HC ... 72
Figure 5.7: Reflectance and standardized reflectance of Aktharma-Pashaly (May 7th 2001). ... 73
Figure 5.8: Reflectance and standardized reflectance of the SWIR part for Aktharma-Pashaly. ... 74
Figure 5.10: Residual spectra of pixels with high RMS error (May 7th 2001). ... 75
Figure 5.11: Mineral abundance maps for Aktharma-Pashaly... 76
Figure 5.12: Unmixing RMS image derived from de-vegetated ASTER ... 78
Figure 5.13: Pie charts pointing out mineral distributions at Aktharma-Pashaly... 79
Figure 5.14: SWIR part of the Convex Hull spectra of the PCA image EMs. ... 80
Figure 5.15: Mineral abundance maps for Lokbatan. ... 81
Figure 5.16: Pie charts pointing out mineral distributions for several mud volcanoes in Azerbaijan ... 82
Figure 5.17: ASTER Lokbatan image reflectance spectra ... 83
Figure 5.18: Mineral abundance maps for Cheildag. ... 83
Figure 5.19: Mineral abundance maps of Cheildag RGB. ... 84
Figure 5.20: Mineral abundance maps for Bozdag-Kobijsky. ... 85
Figure 5.21: Spectral profiles, taken from ASTER for Bozdag-Kobijsky ... 86
Figure 5.22: Mineral abundance maps for Bozdag-Kobijsky RGB. ... 86
Figure 5.23: Spectral plots comparing ASTER data Productive Series Kirmaky Valley. ... 87
Figure 5.24: Mineral abundance maps for Kirmaky Valley... 88
Figure 5.25: Spectral plots comparing ASTER Kirmaky and Surakhany. ... 89
Figure 6.1: Hyperion reflectance spectra for Aktharma-Pashaly ... 97
Figure 6.2: Reflectance and standardized reflectance of Aktharma-Pashaly. ... 99
Figure 6.3: Continuum Removed Reflectance of Hyperion image PCA EMs. ... 101
Figure 6.4: RMS image after the first unmixing ... 103
Figure 6.5: Mineral abundance images maps for Aktharma-Pashaly... 104
Figure 6.6: Mineral mapping results for Aktharma-Pashaly from ASTER and Hyperion... 105
Figure 6.7: Spectral plot comparing ASTER and Hyperion spectra for circular mud vents ... 106
Figure 6.8: Spectral plot comparing ASTER and Hyperion spectra for crateral parts. ... 106
Figure 6.9: Spectral plot comparing ASTER and Hyperion spectra for visible oil seepage... 107
List of tables
Table 2.1: ERS-2 Radar data used for the study. ... 22Table 4.1: Mineralogical composition for onshore mud volcanoes in Azerbaijan.... 45
Table 4.2: PLSR prediction model results ... 52
Table 4.3: ASTER PLSR prediction model results... 56
Table 5.1: ASTER baseline performance after Yamaguchi et al. (2001)... 62
Table 5.2: Overview of the co-registration results ... 65
Table 5.3: Overview of the unmixing statistics... 78
Table 6.1: Spectral feature fitting results for the SWIR part of the spectrum ... 100
List of acronyms
List of acronyms
ASD Analytical Spectral Devices, Inc
ASTER Advanced Spaceborne Thermal Emission and Reflectance Radiometer
CH Convex Hull
DGPS Differential Global Positioning System
DInSAR Differential Interferometric Synthetic Aperture Radar EM Endmember
EO Earth Observation
FWHM Full Width Half Max GCP Ground Control Point GPS Global Positioning System HyMap Hyperspectral Mapper HC Hydrocarbons
IDL Interactive Data Language InSAR Interferometric Synthetic Aperture Radar JPL Jet Propulsion Laboratory
MESMA Multiple Endmeber Spectral Mixture Analysis PCA Principal Component Analysis
PLSR Partial Least Squares Regression PRESS Predictive Error Sum of Squares
PS Productive Series
RER Relative Error Ratio RMSE Root Mean Square Error RPD Relative Percent Difference SAR Synthetic Aperture Radar SEP Standard Error of Prediction SFF Spectral Feature Fitting SNR Signal to Noise Ratio
SR Source Rocks
SWIR Shortwave Infrared USGS United States Geological Survey
UTM Universal Transverse Mercator map projection
VMESMA Variable Multiple Endmember Spectral Mixture Analysis VNIR Visible and Near Infrared
Summary
The fact that Azerbaijan mud volcanoes are closely associated with oil and gas makes their study and identification of the physical and chemical properties of
in-situ mud volcano surfaces important. Although the composition of in-in-situ mud
volcano surfaces can be highly variable, it usually corresponds directly to the presence of hydrocarbons, and the lithology (mainly sand and clay) of the mobilized sediments or parent rocks. Though there are conventional methods to determine compositional information from hydrocarbon bearing sand and clay mixtures, there is a need to continue exploring fast and relatively cheap methods consisting of geophysical, remote sensing (radar and reflectance spectroscopy), and natural radioactivity techniques. In this thesis several methods are explored from data collected at a number of onshore mud volcanoes in Azerbaijan: Aktharma-Pashaly, Bakhar, Bozdag-Kobijsky, Cheildag, Dashgil, and Lokbatan.
In this study geophysical and SAR interferometry methods were used for the first time to assess mud volcano dynamics. Cross-sections from individual subsurface resistivity mud volcano surveys established insight into the scale on which shallow mud volcano processes take place. The results clearly show mud chambers as deep as 8 meters below the surface, as well as mud migration paths (or chimneys) about 0.5 m width.
Assessment of the regional mud volcano activity, based on interferometric SAR, reveals that no large-scale movement is monitored from 1996 to 1999. Atmospheric effects and temporal decorrelation, although to a lesser extent, show that it is practically impossible to retrieve unambiguous volcano deformation information by considering the images separately.
In chapter 3 it has been demonstrated that reflectance spectroscopy is an excellent tool for the screening of iron oxides and hydroxides, carbonates, clay minerals, and hydrocarbons present at mud volcano surfaces, through their distinct absorption features. Examination of XRD results show that the mineralogical composition of Cheildag breccia seems to be separable from the other volcanoes. Gamma-ray spectroscopy information, suggests that Cheildag and Bozdag-Kobijsky mineralogy is altered by active hydrocarbon microseepage (methane emissions) although the differences with respect to Aktharma-Pashaly and Bakhar are small and debatable. This was followed by Partial Least Squares (PLS) regression, a multivariate calibration method, to establish a relationship between mud volcano reflectance spectra and natural radioactivity (chapter 4). Based on the experience for Aktharma-Pashaly, Bakhar, Bozdag-Kobijsky, and Cheildag natural radioactivity is correlated to the presence of illite, chlorite, hematite, gypsum, and carbonates, by means of the shape and exhibitions in the reflectance spectra. For the calibration procedure several spectral pre-processing techniques were compared to analyse the effect of removal/filtering of artefacts, and the best results were obtained by using first derivative spectra using HyMap band passes. Final calibration models, to accurately
Summary
predict total counts and potassium concentration levels within the mud volcano spectra, resulted in qualitative prediction capabilities R2 of 0.82 and 0.58
respectively. The methodology thus allows for rapid determination of natural radioactivity anomalies for a large number of mud volcanoes, and based on the assumption that direct detection of anomalous radioactivity highs or lows is representative for active or inactive hydrocarbon seepage, hydrocarbon activity maps can be created.
Chapter 5 and 6 address the problem of the spectral signatures of mud volcano surface mixtures, assessed from field and image multispectral (ASTER) and hyperspectral (Hyperion) images. Prior to interpretation remote sensing mapping results in terms of geology, the working with multi- and hyperspectral image data sets (such as ASTER and Hyperion) requires knowledge on atmospheric, geometric, and sensor corrections (the pre-processing steps) to apply to the image data to derive data sets which are feasible for physically based image analysis. The corrections applied are (i) transformation of L1R Hyperion data into accurate calibrated radiance (W m-2 sr-1 µm-1) through calibration, bad pixel fixing, VNIR/SWIR alignment,
smile, and destreaking, (ii) transformation from calibrated radiance to apparent surface reflectance using the ACORN atmospheric correction program (Hyperion), (iii) co-registration using cross correlation of near infrared features (ASTER band 3) to allow for comparative analysis between satellite time series or between data from different satellites, and (iv) removal of the crosstalk instrument problem (ASTER), which is caused by light reflected from band 4 optical components leaking into the other SWIR band detectors.
Variable multiple endmember spectral mixture analysis (VMESMA) was used for mapping mud volcano mineralogy, and although the method has been developed for hyperspectral imagers, the method offers greater flexibility and improved performances in unmixing strategies for multi-resolution imagers, such as ASTER. The multiple endmember approach enhanced the stability of 2, 3, or 4 EM models, and in combination with strategic EM selection and standardization of the spectra prior to the unmixing, the reflectance of the volcano surface pixels were accurately modelled. The easy-to-use PCA technique, commonly used in the mineral industry for alteration mapping using Landsat TM, yield valuable information for the unmixing analysis. The results are generally presented either as grayscale images with values from 0.0 to 1.0, which provide a means of estimating mineral abundance, or as color mineral maps showing the spectrally predominant material for each pixel. The mineral assemblage abundance maps show refinement of the distribution of Oligocene to Pliocene sediments, and are valuable products for semi quantitative estimation of Fe, Al, Mg, OH, CO, and SO bearing minerals. Considering the spatial resolution and limited spectral resolution of the ASTER imagery, the abundance images presented in chapters 5 depict the major mineralogy of the alteration zones for a number of mud volcanoes in Azerbaijan, on a pixel basis over continuous ground surfaces. Using associated Hyperion spectra, it was possible to confidently interpret ASTER mixed spectral signals for the distribution and separation of muscovite and illite, even when ASTER band passes do not allow for
direct discrimination. In fact, the images shown can be used in the field as alteration maps to guide exploration activities. In addition, oil seepage is only recognizable by the Hyperion data set by means of exhibitions near 1.72 and 2.3 µm; comparative and associated ASTER spectra fail due to the coarse band pass near 1.7 µm.
Samenvatting
Samenvatting
Het feit dat in Azerbeidzjan modder vulkanen gerelateerd zijn aan olie en gas, maakt het bestuderen en identificeren van de fysische en chemische eigenschappen van modder vulkanen belangrijk. Ondanks dat de samenstelling van de vulkaan oppervlakten erg gevarieerd kan zijn, is het altijd direct gerelateerd aan de aanwezigheid van koolwaterstoffen en lithologie (met name zand en klei) van de gemobiliseerde sedimenten of moeder materiaal. Hoewel er conventionele methoden bestaan om de mineralogische samenstelling van deze olie houdende zand en klei mengsels te karakteriseren, is er de noodzaak voor snelle en betrekkelijk goedkope methoden die gebruiken maken van technieken die hun oorsprong hebben in de geofysica, remote sensing (radar en reflectie spectroscopie), en radioactiviteit. Deze studie maakt gebruik van deze technieken en data die verzameld is op verschillende op land gelegen moddervulkanen in Azerbeidzjan: Akhtarma-Pashaly, Bakhar, Bozdag-Kobijsky, Cheildag, Dashgil, en Lokbatan.
Deze studie maakt voor het eerst gebruik van geofysische en radar remote sensing (interferometrie) technieken om moddervulkaan dynamiek te bepalen (hoofstuk 2). Dwarsdoorsneden van specifieke moddervulkanen, verkregen door geofysische analyse, verschaffen voor het eerst inzicht in de schaal waarop ondergrond processen zich afspelen. De resultaten tonen duidelijk waarneembare modderkamers op een diepte van ongeveer acht meter. Tevens zijn de gangen zichtbaar van ongeveer 0.5m doorsnede waarlangs de modder omhoog beweegt. Regionale analyse van moddervulkaan activiteit met behulp van SAR interferometrie laat geen grootschalige bewegingen zien tussen 1996 en 1999. Met name atmosferische verstoringen, en in mindere mate temporele decorrelatie maken het praktisch onmogelijk eenduidige vulkaan bewegingen uit de beelden te verkrijgen.
Hoofdstuk 3 beschrijft de succesvolle toepassing van reflectie spectroscopie voor moddervulkanen doormiddel van de herkenning van typische absorptie banden voor ijzer oxiden en hyrdoxiden, carbonaten, klei mineralen, en koolwaterstoffen. Dit word gevolg door hoofdstuk 4, waarin XRD resultaten laten zien dat de mineralogische samenstelling van Cheildag breccia verschillend is ten opzichte van die van de andere vulkanen. Aanvullende gegevens over natuurlijke radioactiviteit bij Cheildag veronderstelt dat deze vulkaan onderhevig kan zijn aan actief lekkende koolwaterstoffen, alhoewel de verschillen ten opzichte van de andere vulkanen gering is.
Dit werd gevolgd door Partial Least Squares (PLS) regressie, een multivariate kalibratie-methode, om de relatie te onderzoeken tussen moddervulkaan reflectie-spectra en de natuurlijke radioactiviteit (hoofdstuk 4). Op basis van gegevens van Aktharma-Pashaly, Bakhar, Bozdag-Kobijsky, en Cheildag is natuurlijke radioactiviteit gecorreleerd aan de aanwezigheid van illiet, chloriet, hematiet, gips, en carbonaten. Deze bestanddelen zijn van invloed op de vorm en absorptieverschijnselen in de reflectiespectra. Voor de multivariate kalibratie-methode zijn verschillende spectrale voorbewerkings kalibratie-methoden vergeleken die
verstorende effecten uit reflectiespectra kunnen filteren. De beste kalibratie resultaten werden behaald met eerste afgeleide spectra met de HyMap spectrale configuratie, waarbij total counts en kalium concentraties in moddervulkaan mengsels nauwkeurig konden worden voorspeld met een voorspellingsfout van respectievelijk 0.82 en 0.58. De beschreven methode kan dus worden toegepast voor een snelle bepaling van hoge of lage radioactiviteit anomalieën aan het moddervulkaan oppervlak. De achterliggende gedachte hierbij is dat ervan wordt uitgegaan dat hoge en lage natuurlijke radioactiviteit gerelateerd is aan hoge en lage activiteit van lekkende koolwaterstoffen. Door nu bijvoorbeeld radioactiviteitklassen te ontwikkelen, kunnen PLS analyse resultaten worden gebruikt om met behulp van geografische informatie systemen (GIS) koolwaterstof lekkage activiteit kaarten te vervaardigen.
Hoofdstukken 5 en 6 richten zich op het probleem om karakteristieke spectrale informatie uit moddervulkaan mengsels te krijgen. In hoofdstuk 5 word de analyse verricht met behulp van multi resolutie ASTER beelden, terwijl in hoofdstuk 6 een hyperspectraal Hyperion beeld wordt beschreven. In beide hoofdstukken word uitgebreid aandacht besteed aan de verschillende voorbewerkings methoden om beelden te verkrijgen die concreet analyseer- en interpreteerbaar zijn voor de geologie. De verschillende correctie methoden voor zijn (1) transformatie van L1R Hyperion data naar gekalibreerde radiance (W m-2 sr-1 µm-1) met behulp van
kalibratie, ‘bad pixel fixing‘,‘VNIR/SWIR alignment‘,‘smile‘, and ‘destreaking‘, (2) transformatie van gekalibreerde radiance naar oppervlakte reflectie met gebruik van ACORN atmosferisch correctie programma (Hyperion), (3) co-registratie op basis van de cross-correlatie van nabij infrarode eigenschappen in ASTER band 3, om verschillende ASTER tijdseries en geassocieerde Hyperion te kunnen vergelijken, en (4) herstellen van het ‘crosstalk’ probleem van de ASTER sensor, waarbij licht lekt, vanuit de optische band 4, naar andere banden in het korte golf bereik.
De ontmengings methode, die oorspronkelijk voor hyperspectrale data ontwikkeld is, biedt grote flexibiliteit in ontmengings strategieen, waardoor de methode ook goed toepasbaar is op multi resolutie ASTER data. De ‘multiple endmember’ benadering verbetert de stabiliteit van modellen met 2, 3, of 4 endmembers, waarbij de combinatie met de strategische endmember selectie en standaardisatie van de reflectiespectra, nauwkeurige reconstructie (modellering) van de pixel reflectie mogelijk maakt. De veelgebruike analyse methode in de olie industrie om mineraal alteraties te karteren met behulp van Landsat beelden, de zogenaamde Principal Component Analysise, leverde goede invoer gegevens op voor de ontmenging van de multispectrale ASTER beelden. De resultaten van de analyses geven de verspreiding van kleimineralen, gips, en calciet weer in zogenaamde ‘abundance’ kaarten, die een verfijning in de verspreiding van Oligocene tot Pliocene sedimenten laat zien. Deze kaarten zijn waardevolle producten voor semi kwantitatieve verspreidingen voor Fe, Al, Mg, OH, CO, en SO mineralen, zeker gezien de ruimtelijke en spectrale resolutie van ASTER. In hoofdstuk 6 wordt hierop dieper ingegaan door met behulp van de Hyperion data de gemengde mineralogische assemblages uit ASTER correct the interpreteren. Feitelijk kunnen deze kaarten
Samenvatting
gebruikt worden in het veld om te dienen als ‘gids’ kaart voor exploratie activiteiten. Ook kan met behulp van Hyperion sensor direct olie worden herkend, hetgeen niet mogelijk is met ASTER door haar te brede golfbandbreedte in het korte golf infrarood (band 4).
General Introduction
Chapter 1
General Introduction
1.1 Introduction to the problem
Oil and gas reservoirs leak. Measurable quantities of oil and gas can migrate to the surface through nearly vertical chimneys as a result of reservoir leakage (Schumacher 1996; Saunders et al. 1999), which can pose environmental threats in terms of methane emissions and visible oil pools or tar deposits. On the other hand, hydrocarbon seeps are important in prospecting for oil and gas and much research has been done on the detection and monitoring of seepage. In the area near Baku, Azerbaijan, known oil producing dates back to Alexander the Great, who utilized visible oil seepage at surface and shallow hand dug wells during his campaigns in the IV century BC (Abrams and Narimanov 1997). In Azerbaijan, onshore and offshore hydrocarbon seepage is associated with mud volcanism, which favours hydrocarbon migration to the surface through the nearly vertical mud volcano chimneys. Azerbaijan is probably the area with the world’s densest onshore mud volcano population, within an area of about 16,000 km2 approximately 220 onshore
mud volcanoes have been reported (Guliyev and Feizullayev 1997). The volcanoes act as ‘normal’ magmatic volcanoes with regular hazardous and destructive eruptions. The feeder, or conduit, which can be as deep as 12 km, facilitates mud and oil (if present) migration along chimneys and during an eruption large amounts of mud and oils are emitted. The composition of the mudflows, also referred to as mud breccia, can be highly variable but usually corresponds directly to the nature of the conduit, the presence of hydrocarbons, and the lithology of the mobilized sediments or parent rocks (Kopf 2002).
Against this background the current research was undertaken to (i) identify regional mud volcano dynamics and (ii) to focus on the compositional information of in-situ mud breccia at surface to identify the lithology of the mobilized sediments. The idea is to group mud volcano flow mixture mineralogy into main categories of mineral assemblages typical for mobilized Caspian subsurface sediments which have been subjected to diagenesis by hydrocarbon bearing fluids under varying pressure-temperature regimes during their ascent. Conventional methods for recognizing the physical and chemical properties of a mixture are time consuming and expensive because of extensive laboratory measurements needed (Kemper 2003). There is a need to continue exploring new methods that would bring about identifying particular constituents from a mixture rapidly at low costs. The major advantage of reflectance spectroscopy is the ability to provide a synoptic view on the spatial distribution of minerals, indicating semi-quantitatively the occurrence of hazardous mud flow mixtures released to the environment. Spectroscopy (laboratory, field, or imaging) could provide new insight for recognition and semi-quantification of
minerals based on their influence on the physiochemical properties of the mixture, based on faster and less expensive measurement procedures.
On the small-scale level reflectance spectroscopy can be applied as a fast non-destructive method for the characterization and quantification of the constituents within a mud flow mixture. It is based on the assumption that the concentration of a constituent is proportional to a combination of several absorption features. This study applies multivariate methods for direct detection of parent and hydrocarbon altered mineralogy within the framework of oil and gas exploration. Potentially, alterations or anomalies of minerals at surface can be better understood through the combination of reflectance spectroscopy and the reconstruction of migration pathways from subsurface data.
Characterization and semi-quantification of minerals on a macro-scale level is done through imaging spectroscopy in association with Spectral Mixture Analysis (SMA), which is a means of determining the relative abundance of materials represented in multispectral imagery based on the materials’ spectral characteristics. The reflectance at each pixel of the image is assumed to be a linear combination of the reflectance of each material present within the pixel. In this study SMA is applied on spaceborne systems such as multispectral ASTER and hyperspectral HYPERION image data for sub-pixel determinations of parent rock or hydrocarbon altered minerals present in mud volcano flow mixtures.
1.2 Objectives and workflow of the study
The central aim of this thesis is to analyze onshore mud volcanoes in Azerbaijan in relation to mineral compositional information and dynamics. A thorough analysis of the mud volcanoes using field, subsurface, and remote sensing data, will improve the understanding of the sediments associated with mud volcanoes and mud flows. The following research objectives were defined to meet the principle focus:
Objective 1: To understand the dynamics of the tectonic system driving the mud volcanism through periodic imaging of mud volcano areas in Azerbaijan, using spaceborne Synthetic Aperture Radar interferometry (InSAR) techniques
Objective 2: Reconstruction of the mud volcano shallow subsurface using resistivity measurements and integrate this with surface anomalies mapped using reflectance spectroscopy to better understand the relation between migration and spatial extent of surface features
• Can we identify mud migration pathways in shallow subsurface data? What method can be used to combine and integrate surface and subsurface data? Objective 3: Exploration of correlation between mud flow constituents and mud flow spectral characteristics. A particular interest focuses on the investigation of properties which are of interest for oil and gas exploration
General Introduction • Can we relate the spectral properties of mud breccia to the sources of the
hydrocarbons? What are the spectral scales?
Objective 4: Development and test of models for the prediction of compositional mud breccia constituents with the help of reflectance spectra and natural radioactivity
• What is the role of robust and simple multivariate statistic models to keep the models transferable to data measured in the field?
• What is the relation between detailed pre-processing techniques on the reflectance spectra for the enhancement of important spectral features? Objective 5: Evaluation of spectral mixture analysis for extraction of abundances of mud flow constituents
• What is the relative contribution of advanced unmixing approaches based on multiple endmember sets and standardized variables with respect to multivariate approaches?
• What is the role of pressure and temperature alteration processes in ascending fluids in mud volcanoes and how do they affect imaging spectrometer data?
• Which mechanisms promote the formation of minerals of in-situ mud flow mixtures, and what is the influence of hydrocarbons?
The working steps necessary to derive the quantitative and spatial information about the mud flow constituents are outlined in Figure 1.1. The work consists of three parts, the subsurface analysis, the laboratory/field spectral analysis, and the imaging spectroscopy (spaceborne) data analysis. The division of field spectral analysis and imaging spectroscopy data analysis is imposed mainly by the different data processing steps, since there are several links between the two approaches.
Mud volcano shallow subsurface architecture was obtained by converting electric true resistivity into geological parameters. At the same time during the subsurface surveys the mud volcano surface was measured using reflectance spectroscopy instruments. This data set was used to establish links between subsurface mud volcano architecture and associated venting points to spectral properties of mud flow characteristics.
For the laboratory/field spectral analysis, mud flow samples were collected during field campaigns and analysed with X-ray diffraction to extract valuable mineral information. At the same time during sample collection in the field the mud flow samples were measured using reflectance spectroscopy and gamma-ray spectroscopy instruments. This data set, consisting of natural radioactivity concentrations, mineralogy, and spectral reflectances, was used for the estimation of mud flow constituents based on the spectral properties of the samples. Field spectra were used for ASTER and Hyperion post calibration processing and were inserted into a spectral database as potential endmembers for the SMA. Figure 1.2 overviews the available datasets and field surveys used for this study.
Figure 1.1: Flowchart of the fundamental work steps.
Multiresolution ASTER and HYPERION imaging spectroscopy data were collected from NASA. The ASTER data have been radiometrically and geometrically corrected by NASA, however post calibration processing steps were needed to correct for the crosstalk phenomena. Hyperion data were radiometrically and geometrically corrected and converted into a georeferenced reflectance image. SMA was used for the determination of abundance of different endmembers that contribute to the reflectance in the pixel. The derived mineral maps show the spatial distribution of the mineralogy present mud volcano flow mixtures. This gives a way to separate mud volcanoes in terms of active subsurface mud volcano dynamics (parent rock mineralogy) or active hydrocarbon seepage (typical hydrocarbon seepage mineral alterations).
1.3 Thesis organization
As outlined in the previous sections, deriving semi-quantitative information about clay mineralogy with reflectance spectroscopy in combination with subsurface information comprises a wide range of competences. On the one hand, the geological history of the SCB with its complicated processes over a long period of geologic time under the influence of varying pressure-temperature regimes established a number of primary or secondary clay minerals throughout the depth range along mud volcano chimneys. On the other hand the derivation of quantitative
General Introduction information from laboratory, field, and image data has to be managed. Therefore, chapter 2 presents the Azerbaijan study area. It provides the geologic setting, mud volcano development, and the processes related to parent rock mineralogy and hydrocarbon alteration mineralogy. Chapter 2 provides two case studies for mud volcano dynamics using shallow subsurface surveys and Synthetic Aperture Radar interferometry (InSAR), and discusses the results in terms of the spatial scales on which mud volcano dynamics take place.
Chapter 3 gives a short overview of the fundamentals of reflectance spectroscopy, which are necessary to understand how reflectance spectroscopy can provide compositional information about materials. The spectral properties of materials related to the mud volcanism are presented.
Chapter 4 deals with the analysis of the relationship between mud flow composition as derived form the laboratory analysis and mud flow reflectance and gamma-ray spectroscopy. It presents and analyses mud flow mixtures to assess the influence of hydrocarbon induced environments on the mud flow reflectance. The chapter describes the methods used for the prediction of mud flow constituents based on their spectral reflectance, and finally, it presents and discusses the results obtained. Chapter 5 shows the application of spectral mixture analysis on multispectral ASTER imagery for a number of onshore mud volcanoes. The spatial distributions of mud volcano constituents that mainly contribute to the spectral reflectance properties are discussed.
Chapter 6 addresses the application of spectral mixture analysis on HYPERION hyperspectral data set for derivation of the spatial distribution of parent rocks and hydrocarbon alterations to locate active seep sites and its products. A comparative analysis between HYPERION and ASTER unmixing outcomes is presented.
Finally, in chapter 7 the results are evaluated and recommendations are given for the application of mud volcano dynamics and products using optical and radar remote sensing data in conjunction with geophysical methods. In particular, reflectance spectroscopy in combination with multivariate analysis is discussed as a screening tool for mineralogical provenances, which could provide valuable information in the exploration of oil and gas.
Field Site
Chapter 2
Field Site
This chapter gives a short overview of the geologic setting and mud volcano development in Azerbaijan. Because the focus of this research is to identify the lithology of the mobilized Caspian sediments chapter 2.3 shortly introduces the possible mineralogy alterations, based on literature reviews. Section 2.4 to 2.6 separates the study areas because during two field campaigns in 2001 and 2002 a number of mud volcanoes have been surveyed by using reflectance spectroscopy (2001 and 2002), gamma-ray spectroscopy (2001), and shallow subsurface geophysical data (2002). In section 2.4 we briefly introduce four mud volcanoes on which visible and near infrared (VNIR) reflectance and gamma-ray spectroscopy surveys were carried out to obtain compositional breccia information (the results of these surveys are given in chapter 4). Chapter 2.5 presents the results of shallow subsurface geophysical imaging on two mud volcanoes. Potentially, alterations or anomalies of minerals at surface can be better understood through the combination of remote sensing applications and the reconstruction of migration pathways from subsurface data. In order to direct the research toward a better understanding of the mechanisms triggering and controlling mud volcano, chapter 2.6 discusses interferometric SAR analysis, which can be used to derive surface deformation estimates to provide a regional overview of mud volcano activity.
2.1 Regional Geology
Azerbaijan is situated on the western flank of the South Caspian Basin (SCB). The SCB is located on a portion of the Alpine-Himalayan fold belt (Abrams and Narimanov 1997), roughly between the Greater and Lesser Caucasus and Talysh Mountains in Azerbaijan, the Elburz and Kopet Dag mountains in Iran and Turkmenistan, respectively. The age and origin of the SCB are in dispute, but most published models postulate ages between Jurassic (Zonenshain and Le Pichon 1986) or Paleocene (Berberian 1983), and the SCB is situated on thinned continental crust and Lower Jurassic oceanic crust formed by back-arc spreading (Abrams and Narimanov 1997; Hinds et al. 2004). From the mid-Jurassic into the Neogene, the SCB was a depression on the shelf of Southern Eurasia, and episodic marine restriction led to the deposition of organic-rich calcareous and diatomaceous black shales (Abrams and Narimanov 1997). These upper Oligocene - lower Miocene shales, referred to as the Maykop Suite, are the primary oil source in Azerbaijan. Oil generation from the Maykop Suite appears to have begun during the late Pliocene and continues into the present. Such timing is considered favorable for hydrocarbon entrapment. During the Miocene, when the collision of Arabia took place, a series of complex fold patterns developed and deformed the basin interior (Devlin et al. 1999). By late Miocene-Pliocene, this collision was accompanied by subsidence of the South Caspian oceanic crust (Abrams and Narimanov 1997) resulting in one of the thickest sedimentary columns of deltaic and lacustrine clastics in the world. The
total sediment thickness towards the centre of the basin reaches up to 20 km (Guliyev et al. 1991a; Inan et al. 1997; Lerche et al. 1997; Katz et al. 2000). The last 5.5 Ma Palaeo-Volga and Palaeo-Kura rivers contributed sandy argillaceous alterations, conglomerates, coarse-grained sandstones and claystones to the sedimentary column (Lerche et al. 1997; Morton et al. 2003; Hinds et al. 2004) and the bulk of hydrocarbon reservoirs for Azerbaijan are found in these Pliocene sediments (Figure 2.1). The Pliocene sediments are therefore referred to as Productive Series (PS) and they can be subdivided into two distinct groups (Ruehlman et al. 1995). The early PS is dominated by quartz and minor sedimentary rock fragments typical of the Palaeo-Volga provenance to the north. The late PS contain less quartz, more feldspar, and fragments of both sediments fed by the Palaeo-Kura in the west.
Figure 2.1: General mineral provenance map of onshore Azerbaijan after Morton et al. (2003). The areas of investigation are outlined by the stars.Please consult the enclosed CDROM for a full colour version.
Field Site
2.2 Mud Volcanism
Azerbaijan is probably the area with the world’s densest onshore mud volcano population. Within an area of about 16,000 km2 approximately 220 onshore mud
volcanoes are recorded (Guliyev and Feizullayev 1997). Many of these mud volcanoes are particularly large, up to 400 m altitude, they erupt regularly and episodically, and the temperature of the expelled materials is approximately 21-23°C. The major factors causing extensive mud volcanism in onshore (and offshore) Azerbaijan are tectonic overpressure, density inversion, sediment loading and gas hydrate dissocation (Guliyev and Feizullayev 1997; De Lange and Brumsack 1998; Lerche and Bagirov 1998; Milkov 2000; Aloisi et al. 2000a, 2000b; Kopf 2002). Figure 2.2, adopted from (Kovalevsky 1940; Inan et al. 1997; Lerche et al. 1997), shows a general mud volcano cross section in the western part of the SCB. The figure clearly reveals that mud volcanoes can have conduits as deep as 13 km and that ascending fluids pick up parent material from Jurassic to Quaternary age. Mud volcanoes act as ‘normal’ magmatic volcanoes, typically taking the form of a truncated cone with regular eruptions. Mud volcanoes feed from the buried body of sediment that form the subsurface of the SCB. In order to allow these soft and unconsolidated oil-rich sediments to ascend, the primary prerequisite is the presence of density inversion due to mineralogical differences as a function of sediment provenance (Kopf 2002).
Figure 2.2: General mud volcano cross section in the western part of the SCB, adopted from Kovalevsky (1940), Inan et al.(1997), and Lerche et al. (1997). The figure clearly reveals that mud volcanoes can have conduits as deep as 13 km and that ascending fluids pick up parent material from Jurassic to Quaternary age.
Common minerals in the Caspian successions such as gypsum, halite, kaolinite, smectite, and vermiculite groups have densities lower than quartz or feldspar and have the capability to incorporate large volumes of water in their mineral structure. Consequently their buoyancy relative to the other Caspian sedimentary rocks suggest that strictly no additional driving force other than this density inversion is needed to allow ascent. This rather slow process leads to slow sediment ascent and additional driving forces are required to explain the massive explosions commonly noticed for onshore Azerbaijan mud volcanoes. The second prerequisite for sediments to ascend is sediment loading (Lerche and Bagirov 1998; Kopf 2002). These authors mention that very rapid subsidence of the SCB leads to large amounts of clay-rich sediments with abnormally high porosities for its depth, often referred to as overpressured or undercompacted fluids. Fluid overpressures are known to play a crucial role in faulting, which is also a prerequisite for mud volcano development. Although a number of factors cause undercompaction, gas hydrate dissociation is considered the most prominent significant one (De Lange and Brumsack 1998; Lerche and Bagirov 1998; Milkov 2000; Aloisi et al. 2000a, 2000b; Kopf 2002). Hydrates of fixed composition like methane, ethane or propane may exist under particular pressure-temperature (PT) conditions, and under the impact of neotectonic processes, PT conditions may change and hydrates may be dissociated and released as gas and water. The dissociation can take place gradually or explosively, depending on how fast the pressure drops or temperature increases. A combination of high hydrate concentrations and low thermal conductivity of mud leads to low temperature gradients. This can contribute to hydrates concentrating at the crest of the volcano, which, in turn, can lead to massive explosions.
During such an eruption large amounts of the Caspian argillaceous materials (containing oil and gas) are emitted to establish typical mud volcano surfaces in terms of a series of recent and older mud flows with characteristic tongue-shaped forms. Also on the crateral parts, active vents of mud with water, oil, and gas (if available) are commonly noticed (Hovland et al. 1997). Depending on the amount of water, different types of active vent sites can form, such as gryphons (small steep little volcano cones) and salses (circulare flat vents). This will be discussed in more detail in chapter 2.4, when the study sites are described.
2.3. Geochemical processes
2.3.1 Ascending mineralogy along mud volcano chimneys
During ascend the mud mineralogical composition can take a number of forms due parent material, due to different pressure and temperature differences, as well as the presence of hydrocarbons. The deeply buried sediments of the SCB exhibit the distinctive characteristic of argillaceous oil reservoirs, i.e. the mineral composition is represented by harder minerals such as chlorite, illite, and kaolinite (Geology Institute of Azerbaijan (GIA), pers.comm.) and the level of catagenesis hardly increases with depth. In other words, the mineral composition of ejected mud volcano material is almost identical to that of the Pliocene clays (eastern shelf of the
Field Site Caspian sea) or Oligocene to Miocene clays (Lower Kura depression). The main sediment source areas during accumulation of the Pliocene deposits of the western shelf were the Great and Lesser Caucasus and Talysh mountains. These areas contained substantial Mesozoic and Cenozoic volcanigenic rocks which acted as sources of montmorillonite-rich sediments. Buryakovsky et al. (1995) showed that Oligocene to Miocene deposits are characterized by montmorillonite and mixed layered clay with chlorite, hydromica, and ash material, and that montmorillonite is present in large amounts to a depth of 6200m. Therefore these authors question that the level of catagenesis hardly increases with depth, because their findings show that it is difficult to assess clay mineralogy due to the various PT regimes throughout the Caspian history.
2.3.2 Hydrocarbon-induced environment
To assess the subsurface mineralogical content from mud volcano flow mixtures we have to consider the fact that mud volcano vents are closely associated with hydrocarbon seepage. Seepage is perceived as a near vertical process resulting in hydrocarbons migrating along chimneys (Saunders et al. 1999). The visible products of such seepage, i.e. oil and tar deposits, are found at a number of mud volcanoes and are generally referred to as hydrocarbon macroseepage. Hydrocarbon microseepage are invisible trace quantities of light hydrocarbons seeping to the surface, and methods for detection focus on secondary effects resulting from such seepage. Bacterial oxidation of light hydrocarbons brings about significant changes in the Ph and Eh environment near the vicinity of the seep. This establishes locally anomalous redox zones that favour the development of a diverse array of chemical and mineralogical changes, which are therefore mineralogy and chemically different from laterally-equivalent (Schumacher 1996; Saunders et al. 1999). These authors mention that resulting mineral alterations include the formation of calcite, pyrite, uraninite, elemental sulfur, magnetic iron oxides and iron sulfides, bleaching of red beds, clay mineral alterations, electrochemical changes, radiation anomalies, geomorphic anomalies, the edge anomaly of adsorbed or occluded hydrocarbons in soils and Delta C (ferrous carbonate), and biogeochemical and geobotanical anomalies. Because a single paragraph cannot cover the topic of subsurface diagenetic mineral alterations in a hydrocarbon-induced environment adequately, the reader is referred to (Saunders et al. 1993; Tedesco 1995; Schumacher 1996; Saunders et al. 1999; Schumacher and LeSchack 2002) and the references therein for more detailed discussions.
2.4 Study sites
This paragraph gives an overview on the geologic setting of Aktharm-Pashaly, Bakhar, Bozdag-Kobijski, and Cheildag mud volcanoes which have been surveyed by reflectance spectroscopy in association with gamma-ray spectroscopy (Figure 2.3). The results of these surveys are discussed in chapter 4. The descriptions here are based on Yakubov et al. (1971) and Hovland et al. (1997) in association with field surveys during 2001 and 2002.
Figure 2.3: General geologic map and studied mud volcanoes of the investigated area. Synthetic cross sections (Yakubov et al. 1971) through Aktharma-Pashaly, Bakhar, and Cheildag show stratigraphical variation. Location of the mud volcano sampling points and the mud volcano geology units identified are displayed as artist impressions. Please consult the enclosed CDROM for a full colour version.
Field Site Lokbatan and Dashgil mud volcanoes were studied with reflectance spectroscopy in assocation with geophysical methods, and the volcano descriptions and results are presented in chapters 2.5 and 2.6.
2.4.1 Aktharma-Pashaly
Aktharma-Pashaly is one of the largest onshore mud volcanoes in Azerbaijan, and is situated about 90 km southwest of the city of Baku (Figure 2.3). The elevation difference between the lower Kura valley (the Shirvan sloping plain) and the volcano, is about 300 m and the volcano has the form of an asymmetric cone. The volcano summit can be considered as a smooth oval plateau of about 4km2
(estimated from recent satellite imagery) on which thick flows of breccia has flowed in the direction of the plain. The plateau is surrounded by a rampart and the volcano slopes, especially in the southwest, are dissected by very steep gullies. The geological structure of Aktharma-Pashaly involves the deposits of Pliocene-Apsheron and Quarternary complexes. Tectonically the volcano is confined to the joint of the axis of 3 anticlines (Kalamadyn, Great Kharami, and Lesser Kharami) which fold Middle Pliocene deposits and are cut by axial thrust faults.
The mud volcano cover occupies an area of about 1500 ha and the thickness of the breccia cover varies from 100-300m on the periphery, up to 600m in the central part on the basis of drilling records. The width of the volcanic vent is up to 700-750m and the volume of the mud breccia ejected is 16*109 m3. In the breccia fields clasts
of Late Cretaceous and Eocene age, black dolomites, yellowish clay of Miocene age (Maykop), and Pliocene sandstones and clays are commonly found. Aerial photography (Figure 2.4) recognizes a number of circular mud vents, from which the centre circular vents can be related to recorded eruptions of 1948 and 1956. ASTER satellite images from 2001 and 2002 is able to recognize the 1982 major eruption (Figure 2.4).
Figure 2.4: Aerial photography (left) and ASTER spaceborne (right) overview of Aktharma-Pashaly summit with its characteristic concentric mud flows and lateral joints. The Aerial photography is a co-registrated mosaic of three aerial photos through cross correlation of the spectral information (Hill and Mehl 2003). The ASTER image from May 5th 2001 is represented as grey scale image and the four main
active vent sites are given in latin numbers. Please consult the enclosed CDROM for a full colour version.
The huge flows and associated concentric ring fractures apparent from Figures 2.3 and 2.4 and imply that the volcano was characterized by very much more powerful eruptions in the geologic recent past. Within the volcano summit four areas with active vents such as gryphons and salsas were identified: (i) south-east group, (ii) centre group, (iii) northwest group, and (iv) western group.
The southeast group (I)
The southeast group is characterized by more than 50 gryphons less then a few meters high, and almost all emit gas, water, mud and oil. The level of activity is relatively low, and the area is partly covered by vegetation. The gryphons rest upon weathered breccia of more ancient eruptions.
The central group (II)
About 750m northwest of the southeast group, around 50 gryphons along a 290 degree azimuth are situated. The general level of activity is low and many gryphons are partially eroded revealing oil seaked mud breccias within. The active gryphons emit gas, mud, water, and thick oil, and a major recent flow of oil has formed a 50x20m kir field, the tarry residue marking the remains of a former oil lake.
The northwest group (III)
This group is situated about 450m northwest of the central group along an azimuth of 320 degree. The group is characterized by concentric breccia fields, from various old eruptions, having diameters of about 400m, 210m, and 150m, the later formed on September 25th 1948. Volcano reactivation in 1982 established new breccia
fields, which covers some of the earlier covers (GIA, pers.comm).
The western group (IV)
This area is situated about 700m south of the northwest group or 500m southwest of the centre group. Three flows were identified with diameters of 220, 140, and 100m, from which the later flow is about 0.4m thick and formed as the result of mud volcano activation in 1982.
2.4.2 Bakhar
Bakhar mud volcano is situated on the eastern tip of Cape Alyat, approximately 57 km southwest of the city of Baku (Figure 2.3). It forms a circular hill rising about 70m above the surrounding coastal plain. The mud volcano covers an area of about 65 ha with a thickness of approximately 50m. The eastern flank is marked by steep cliffs, most probably developed in the recent past when sea levels were slightly higher.
The volcanoes geological setting is at the intersection of a longitudinal fault and a transverse fault. The mud volcano breccia includes thick beds of the upper part of the PS with clasts of predominantly sandstone, often oil saturated with a strong petroliferous odour. Earlier work by GIA recognized clasts of Late Cretaceous (Cenomanian), Eocene, Oligocene, Miocene, and Pliocene age.
Field Site Since 1823, eight strong eruptions have been recorded, with spectacular flames up to 150m high. The volcano covers an area of about 66 ha and it forms a circular rise with an absolute height of 28.6m. The average thickness of Bakhar is between 20-70m. There are three gryphon fields with gryphons of a few metres to about 15 meters high. In 1992 a big eruption took place and ejected approximately 200,000 m3 mud covering an area of about 8ha, with an average thickness of 2m. Since then the centre of the eruption is characterized by a cluster of moderately active gryphon field of approximately 30m across, which gives little clue to the violent character of the initial eruption.
2.4.3 Bozdag-Kobijsky
The Bozdag Kobijsky mud volcano, also referred to as Bozdag-Kobi, is situated on the Apsheron peninsula, approximately 20km north-west of Baku (Figure 2.3). The volcano can be characterized by an elongated rampart with a latitudinal trend, with the mud volcano located in the centre of it. The volcano itself consists of two groups, one of these groups trends northwards while the other trends approximately 1000 m eastwards of the former one. Seven large, up to 3-3.5m, and 5 small extinct mud cones are located on the crateral rampart of the volcano. The geological structure of Bozdag-Kobijsky involves the deposits of Paleogene-Miocene complex. Tectonically, the volcano is confined to the forking of two anticlines which stretch to the southeast (Shabandag-Lokbatan-Putinskaya) and northeast (Khurdalano-Binagady) respectively.
Several eruptions have been recorded and in between 1827-1957 the volcano erupted 5 times (1827, 1894, 1902, 1953, and 1957). The mud breccia thickness ranges within 1-5 meters, the volume of the ejected breccia from the recent eruption is 9000 m3.
The main reason to study Bozdag-Kobijsky is that the breccia fields have a different ‘look’ compared to the other volcanoes. The surface of the breccia fields appear more irregular and ‘dry’ and it has been postulated that the breccia fields are formed due to built-up pressure in the subsurface, similar to the release of toothpaste from a tube, in a combination with the filling of the mud chambers. Evidence for such built-up pressure in the subsurface is the recorded vertical displacements of about 40cm at surface.
Finally, the mud volcano naming convention, Bozdag means grey mountain, reveals valuable breccia compositional information for reflectance spectroscopy in terms of the presence of iron or other related minerals causing the grey colour.
2.4.4 Cheildag
Cheildag mud volcano is situated about 52 km westsouthwest of the city of Baku along a azimuth of about 230 degrees (Figure 2.3). The volcano is situated along the faulted part of an anticlinal fold. At present, the volcano consists of four groups of gryphons and salsas, which give off gas and oil films, and the clasts contain blocks of grey medium-grained sandstones, sometimes impregnated with oil. The venting
points are located within the boundaries of an ancient crater of the violent eruption in 1870. The total area of mud breccia distribution is 1349ha. Well drilling data and structural mapping estimated the volcano depth around 80m in the centre to 20-30m at the peripheral parts.
2.5 Mud volcano shallow subsurface
2.5.1 Method
The purpose of mud volcano electrical surveys is to define the mud volcano architecture in terms of mudflows or eruptions through time. By injecting an electric current into the ground through two current electrodes, the resulting voltage difference at two potential electrodes can be measured, and the apparent resistivity of the volcano subsurface is derived. The apparent resistivity is an average value for the ground taken as a homogeneous half-space (Loke 2000). To determine true subsurface resistivity an inversion of the measured apparent resistivity is carried out by using the smoothless-constrained least-squares method on rectangular blocks (deGroot-Hedlin and Constable 1990; Sasaki 1992). The apparent ground resistivity is related to various geological parameters such as the mineral and fluid content, porosity, and degree of water saturation in the rock (Daniels and Alberty 1966; Keller and Frischknecht 1966). For example wet soils and fresh ground water resistivity values vary between 1 and 100 Ohm.m-1. Clayey soil normally has lower
resistivity values than sandy soil because of the lower porosity, the degree of water saturation, and the concentration of dissolved salts. Sedimentary rocks in general show resistivity values between 50 and 4000 Ohm.m-1.
2.5.2 Results Bozdag-Kobijsky
In 2002, a 72m long 2D electric resistivity survey with electron interval of 1m at Bozdag-Kobijsky mud volcano using pole-dipole configuration is carried out. Figure 3.5 plots the 2D result up to 20 meter below the surface with varying resistivity between 1 to 41Ωm-1, represented by a colour ramp from blue to purple.
Intermediate cases will be represented as intermediate colours of the spectrum from red to blue to purple.
The survey identifies a mud chamber at the left side of an interpreted fault, starting about 8m below the surface and about 4 m wide (Figure 2.5). Present vents, a gryphon at electrode 28 and a salsa at electrode 34, can be connected to the mud chamber (blue dotted lines) showing the same heading as the subsurface fault. This could indicate that mud migration mechanisms might be confined to faults present in the area. Bozdag subsurface architecture seems to have a symmetrical shape, which can be the result of the pole-dipole measuring setup (Loke 2000), but two older mud volcano eruptions are identified (Figure 2.5, numbers 1 and 2).
Field Site
Figure 2.5: Bozdag-Kobijsky resistivity subsurface measurements with geological interpretation. Please consult the enclosed CDROM for a full colour version.
2.5.2 Results Lokbatan
Lokbatan is one of the most studied onshore mud volcanoes due to its spectacular eruptions, it is intimately associated with hydrocarbon production, and the geographical situation close to the city of Baku makes the volcano easy to reach (Figure 2.6). Accurate 3D insight into mud volcano architecture is provided by a 3D subsurface survey over the Lokbatan eruption of 2001 with a vertical and horizontal resolution of 1 meter. A 5x11m grid next to the major vent of the 2001 eruption is sampled to image the migration pathway of this major eruption. It was not possible to locate the grid completely over the venting point because the vent was still burning and giving off major quantities of gas. Figure 2.6 plots the 3D subsurface of Lokbatan with varying resistivity between 1 to 41Ωm-1, represented by a colour
ramp from blue to purple, and intermediate cases will be represented as intermediate colours of the spectrum from red to purple. The resistivity values typically indicate a clay type of subsurface material composition (Loke 2000) and the liquid mud parts (blue colours, low resistivity) are connected to the surface with a nearly vertical small pipe, the feeder channel of mobilized sediments. The purple coloured upper parts of the image show the exact places where the previously burning gas seepage was present.
2.5.3 Results Dashgil
Dashgil mud volcano is situated about 10km westwards of Bakhar mud volcano, approximately 60km southwest of the city of Baku (Figure 2.7). The crateral field contains approximately 80 active and extinct gryphons and salses, which intensively giving off gas and minor quantities of thick mud oil films. Two line searches, and 72m long and perpendicularly distributed, were carried out to measure the resistivity of number of active and inactive gryphons withih the crateral field. Figure 3.7 shows the results of the two line searches (I-I’ and J-J’) and the low resistivity values indicate that Dashgil subsurface is more wet than those of Bozdag and Lokbatan. Some high resistivity spots are present in the 2D survey of 12A, which are probably attributed to the presence of clasts (calcite, limestone).
Figure 2.6: Lokbatan subsurface resistivity. The white polygon on the aerial photograph shows the spatial extension of the mud flow after the 2001 eruption (DGPS measurements). The black inset on the left picture shows the measurement grid on the volcano surface. The view perspective from the surface towards the mud volcano interior (left) and view perspective from inside the volcano towards the surface (right). Possible mud migration pathways can be distinguished in terms of low resistance values. Please consult the CDROM for a full colour version.
Field Site
Figure 2.7: Dashgil resistvitiy subsurface measurements. The oblique view (artist impression) from the north shows a natural oil pool (A), drilling derrick (B), cluster of gryphons (C), clastic lobs (D), salses (E and F), string of sinter mounds (G), and drainage pool (H) after Hovland et al. (1997). The small inset shows the location for the resistivity measurements I-I’ and J-J’. Please consult the enclosed CDROM for a full colour version.
