HYDROCARBON MICROSEEPAGE DETECTION AND IMAGING SPECTROSCOPY IN
AZERBAIJAN
K.H. Scholte (Ph.D. student)
Faculty of Civil Engineering and Geosciences
Department of Applied Earth Sciences
Section Earth Sciences
The objective of this research project is to study the possibilities of Remote Sensing for leaking petroleum
reservoirs. We use remote sensing to understand mud volcano evolution and dynamics and associated
hydrocarbon seeps in terms of 1) the spectral behaviour of mud volcano ejecta by assessing remote
sensing and imaging spectrometry and 2) we try to relate mud volcano spatial deformation to stressfields,
subsidence and chimneys by assessing InSAR interferometry and shallow seismics.
Introduction
Oil and gas reservoirs leak. This poses environmental threats and the emission of the greenhouse gas
methane at seeps contributes an unknown volume to global change processes. In Azerbaijan oil and gas
seepage is intimately associated with mud volcanism. Modern theories suggests that mud volcanism is
typical of basins which are undergoing very rapid subsidence such that the expulsion of pore fluids from
the lower levels does not keep pace with the rate of sediment accumulation. This leads to a density
contrast between the overlying and underlying deposits. With the triggering effect of tectonic processes,
the overlying deposits may loose their integrity and the underlying argillaceous sequences may be forced
upwards, resulting in the creation of a piercement structure (clay diapir) or a mud volcano.
Mud volcanic eruptions can be considered as a mixture of source rocks, productive series, oil, water and
other sediments from the subsurface, represented by mixed mudflows on the earth surface. Mudflows can
reach several km in lengths, several meters thick with flow widths of up to several hundreds of meters.
Studies on the properties of these features show that the waters are mainly alkali. The oils show a small
range in δC13, indicating a similar source. The gases predominantly exist of CH4 (Methane) (90-95%) but
also small amounts of CO2 (6-7%), and H and HS (1%) are found. Regional present source rocks are
Maykop dark shale and chokrak sandstone.
Long-term leakage of hydrocarbons can establish locally anomalous redox zones that favour the
development of a diverse array of chemical and mineralogical changes. The resulting alterations include
e.g. the formation of calcite, pyrite, uraninite, elemental sulfur, and certain magnetic iron oxides and iron
sulfides and bleaching of red beds.
In principle many mineral alterations as well as mud volcano fresh and weathered flows can be mapped
using imaging spectrometers. Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) on
Landsat Thematic Mapper 7 will be used to map natural hydrocarbon seeps and associated mud flow
dynamics. Spectral unmixing techniques strive at finding partial least squares solutions to the linear mixing
of spectral components in order to derive fractional abundance estimates of selected endmembers. Remote
sensing thus offers possibilities to locates oil seepage, regional source rock distributions, and mud flow
distributions in terms of relative age (weathering conditions), new-growth of minerals, aiming to find a
relation between mud flow type variations and different eruption events controlled by recent tectonic
events.
This research project started in September 2000 and will span 4 years to September 2004
Results in 2001
A detailed field survey is carried out in spring 2001 and the data is stored in a GIS environment to carry
out spatial analyses. For all the different oil mud volcano properties we stored 1) field spectrometer data
(in between 0.5-2.5m), 2) field radionucliden data (K, U, Th), 3) surface soil temperature, 4) soil and
mineral moisture content, 5) exact spatial position DGPS.
Pixel Purity Analysis on the hyperspectral field data is carried out and 70 spectrally pure endmembers are
found. Mud volcano properties and source rocks have spectrally significant absorption features that enable
us to use them as input spectra for VMESMA.
A 3 endmember-model is calculated to accurately describe pixels in terms of endmember abundances. Mud
volcano spectra of Landsat TM data is successfully classified using VMESMA in terms of different
endmember combinations of pure endmembers. Fresh mudflow, water, and Maykop source rock spectral
signatures describe for the greater part the mud volcano craters. Hydrocarbons were not directly detected
due to the low spectral and spatial resolution of the satellite data. Promising mineral alteration
identification and regional source rock mapping is achieved.
Research plan for 2002
 In Cooperation with the Faculty of Geodetic Engineering, satellite radar interferometry will be used to
investigate recent mud volcano surface deformations and movements.
 To find a concept for a process based model to integrate sub surface seismic data with surface spectral
data to dynamically model surface measurements.
Completed Courses
 tg001: An overview of standard seismic processing applications
 tg211: Geological outcrop analysis
 Private language course in Russian (1)
Publications in 2001
Scholte, K.H, A. Gieske, F. van der Meer, S.M de Jong; Geometric correction of DAIS-7915 experimental
data by means of Bivariate Kriging, International Journal of Remote Sensing, subm.
Meer, F. van der, W. Bakker, K. Scholte, A. Skidmore, S. de Jong, J. Clevers, E. Addink, G. Epema;
Spatial scale variations in vegetation indices and above-ground biomass estimates: implications for
MERIS. International Journal of Remote Sensing, 22(17): 3381-3396. ISSN 1366-5901.
Proceedings in 2001
Scholte, K.H., F. van der Meer, S.B. Kroonenberg, M. Malkhazov, E. Aliyeva, I. Guliev, D. Huseynov;
Variable multiple spectral mixture analyses to map onshore oil mud volcanoes, Azerbaijan. ESF
workshop on hydrocarbon seeps, greenhouse gasses and tectonics. (27-28 august 2001, Delft).
Workshop and Poster presentations in 2001
Poster presentation at the EAGE 63rd Conference & Technical Exhibition — Amsterdam, The Netherlands,
11 - 15 June 2001.
Education
Supervised the practical part of the first year course ta1940 Remote Sensing.
Supervised M.Sc. thesis
None.