Author: Michael Hall, Senior Geologist, Airbus Defence and Space
Satellites are a recognised method for gathering data remotely and understanding surface characteristics of both land and ocean, providing a unique insight when developing hydrocarbon reserves.
Gathering such satellite derived Earth Observation (EO) data offers focused geospatial intelligence to support oil and gas projects as they progress from exploration, through development, production down to decommissioning stage.
Applications relevant to exploration include geological interpretation, infrastructure and vegetation mapping, terrain assessment and the identification of natural oil seeps. A key benefit of using satellites is the effective targeting of field surveys and seismic collection.
Additionally, the use of EO data is particularly relevant where exploration is occurring in remote areas with difficult or hazardous access, where personnel, equipment or the environment may be put at risk during field activities.
Latest satellite technology
Utilising EO data for supporting exploration activities has increased in recent years in parallel with the technological progression in satellite sensor technology, coupled with the use of satellite constellations where two or more satellites with similar capabilities are operated together.
These advancements have led to greater spatial, spectral and temporal resolution giving an increase in detail that can be discerned, the number of spectral bands over which information can be collected and the frequency at which an image can be obtained.
Optical and radar satellites
Satellite systems for EO centre around two main categories: optical and radar.
Their primary characteristic is their spectral and spatial resolution depending on the specific sensor, with a range of pixel sizes from tens of metres to less than half a metre.
Many of the optical satellites allow multiple images to be acquired from different angles as the satellite passes over a target area in order to produce a Digital Elevation Model (DEM), which is a three-dimensional representation of the ground surface. A DEM can be processed to calculate slope angles and interpreted to identify geomorphological and structural features.
Optical satellites typically operate in the visible and near-infrared part of the spectrum. However, they can have extended multispectral capabilities acquiring data in a number of wavelength bands not visible to the naked eye, giving additional insight into vegetation and lithological characteristics including mineralogy.
These multispectral bands are typically acquired at coarser resolutions than the visible wavelengths.
Whereas optical satellites rely on reflected or emitted electromagnetic radiation initially sourced from the sun, radar sensors on satellites are active and send pulses of microwave energy to the earth’s surface and record the return signal.
Individual radar sensors, such as TerraSAR-X, operate at a particular wavelength and offer high resolutions down to 0.25 metres. These sensors are independent of cloud coverage, sensitive to identifying surface characteristics including texture and geomorphology, whilst also allowing DEM generation.
Satellite base datasets
Satellite imagery and DEMs can be considered as key base datasets for EO oil and gas applications, from which a number of value-added products and services can be derived.
Imagery used for oil and gas applications typically range from around half a metre resolution for detailed studies to 15m resolution for more regional applications.
In terms of elevation data, available DEM datasets include SRTM and ASTER GDEM with 30-metre grid spacing and are typically suited to regional studies.
Increasing in accuracy and resolution, commercial DEMs include the recently released WorldDEM™, a global elevation model at 12 metre grid spacing, allowing more subtle terrain features to be identified.
Radar derived DEMs can be generated using radargrammetry or interferometry techniques with grid spacing of approximately 10 metres and are particularly applicable in areas where frequent cloud cover would limit an optical approach.
Where higher resolutions and accuracies are required, bespoke models at 1m grid spacing can be generated using very high resolution stereo satellites, giving the greatest accuracy levels with the use of surveyed ground control points.
The value of EO data in supporting oil and gas exploration is in the interpretation and analysis applied to the base imagery and elevation models, including geological interpretation and seismic planning as outlined in the following sections.
Geological interpretation and assessment
An understanding of surface geology is valuable in screening areas for exploration and targeting seismic acquisition and fieldwork more effectively.
Many areas of exploration have a lack of existing geological mapping at a suitable scale or accuracy, with prospective structures potentially absent or inaccurately positioned. In addition, locations may be challenging to access for logistical or security reasons, which makes the targeting of field surveys particularly relevant.
The use of EO data for geological interpretation is well established and can be performed at a range of scales, from regional down to an individual license block or structure. Regional studies may be undertaken on a multi-client basis and are available for many key regions and exclusive studies over individual licence blocks.
For example, the East African Rift System can be viewed as an exploration hotspot with onshore discoveries in the Albertine Rift and Turkana County, Kenya and offshore discoveries in Tanzania and Mozambique. Here, a regional multi-client geological study covering approximately 4.5 million square kilometres is providing exploration companies with a consistent onshore geological interpretation of structure and stratigraphy. This together with the identification of oil seeps on the rift lakes and offshore, forms an important baseline of information to support exploration.
The primary source of this information is satellite derived, including radar data for identifying slicks on water-bodies, as well as optical data and digital elevation model (DEM) data for onshore geological interpretation.
In a new study Airbus Defence and Space assessed the nature of the petroleum-rich Zagros region in Iran using remote sensing data for a detailed fracture reservoir study. The study includes detailed mapping and analysis of the distribution, intensity, relative geometry, continuity, connectivity and structural settings of structures and faults for seven sub-areas selected across the region, together with major structural features of the Asmari Formation’s reservoir quality of fractured carbonates.
Analysis and interpretation of satellite imagery is now almost exclusively undertaken in a digital environment, using image processing software and geographic information systems (GIS). Geological interpretation from remote sensing data of structural features, stratigraphic boundaries and superficial geology relies on the assessment of a range of image and elevation model features including geomorphology, spectral signatures, texture, vegetation and drainage patterns. Although the primary information source is the available EO datasets it is important that remote sensing geological studies are undertaken in reference to existing mapping, any field data and published information.
A typical structural interpretation would include the capture of features such as dip and orientation of bedding surfaces, surface trace of major and minor faults, their classification and indication of relative sense of displacement. Fold axial surface trace of fold structures, sense of vergence and direction of fold plunge can also be identified.
Assessment of fracture orientation and density is often carried out as part of analogue studies where target reservoir rock may outcrop in other parts of the basin outside the licence block.
Quantification of dip and strike values is possible where sufficiently detailed DEMs are available and the target area contains suitable structurally controlled geomorphological features. Algorithms have been developed which combine, for example, digitised bedding planes, represented by ‘flat iron’ features and elevation values to calculate approximate dip and dip azimuth values, assisting with three-dimensional modelling.
Lithological discrimination can be based firstly on the visual pseudo-colour appearance on the imagery, using non-visible parts of the electromagnetic spectrum and relating the appearance to existing geological maps, and secondly through further analysis such as band ratios which give a certain degree of mineral identification. Mineral identification capabilities are linked to the available spectral information, with capabilities generally increasing with the number of spectral bands over which a sensor is collecting data.
EO sensors with suitable spectral bands in the Short Wave Infra-Red (SWIR) are preferred due to the particular absorption characteristics of different minerals in this part of the spectrum for lithological discrimination. However, textural and geomorphological features can also assist in mapping lithological units and particularly when vegetation cover is dense. In cases of dense vegetation more emphasis is placed on techniques, which emphasise these variations in terrain and texture, such as the use of enhanced elevation models and radar data.
In desert areas, sand cover can obscure the underlying geology and structurally controlled drainage patterns and in this situation longer wavelength radar data can be used to gather information on the shallow subsurface.
Controls on positioning seismic acquisition relate to the nature and distribution of a range factors including geology, terrain, infrastructure and land use and these influences, can be assessed with the support of satellite-sourced information. In order to understand the spatial variation in slope angle, representations of the terrain in the form of DEMs are used to assess potentially accessible areas.
Land cover information is required to assess areas that are environmentally sensitive, or potentially hazardous, with the aim of reducing risk and minimising the impact of seismic collection. Hazardous areas include areas prone to flooding, subsidence or instability such as sand dune migration or mass movement.
In addition, insights into the frequency of previous flooding events can be established from archive satellite data. Equally, an understanding of the distribution and extent of habitation and agricultural activity can be used in survey planning to minimise the impact on local populations.
Quantitative analysis of variation in terrain and land-cover and the interaction between them allows a more accurate understanding of the factors influencing seismic planning. In order to effectively assess multiple geo-information datasets appropriate to seismic planning, GIS is increasingly used, offering the functionality to combine and weight individual data layers to aid the establishment of optimum routes.
Ultimately, satellite imagery and derived elevation models are making an important contribution to reducing risk at each stage of the oil and gas project lifecycle including exploration, with a range of capabilities suitable to specific environments and requirements. This is particularly important in times of falling oil prices and the industry’s ongoing efforts to increase operational efficiency.