Surveying a desert region in Egypt
In the Egyptian Western Desert, almost 700 km west of Cairo, Apache Corp. planned a seismic study in the Ghazalat Basin which contains plateaus and steep escarpments. Prior to the survey, WesternGeco included satellite remote sensing as part of a multi-physics, near-surface characterization to establish the risk for logistics and acquisition (1).
The near surface comprises two formations: the Moghra and the overlying Marmarica (Ghazalat Lithology). The lowermost portion of the Marmarica Formation has alternating hard limestone and soft claystone layers, which transitions into a massive limestone in the upper part of the Marmarica Formation. The underlying Moghra Formation consists of an alternating sequence of sandstone and claystone layers. Both of these formations outcrop in the Ghazalat prospect area.
A DEM image of the area was available from ASTER satellite data with lateral and vertical resolution of 30 m, sharpened to about 17 m using the higher-resolution pan band. About 10% of the study area is in the Qattara Depression about 80 m below sea level, bordered by an escarpment of 100 to 120 m reaching a plateau at about 50- to 60-m height. The plateau makes up about 50% of the study area, reaching elevations greater than 250 m above sea level in the north.
In addition to the large escarpment bounding the depression, other escarpments are present. These were determined using an eight-direction edge-detection algorithm (2). The escarpments can be overlain on the terrain-height map to obtain a topographic classification map (Figure 6 - Ghazalat topoMap).
The lithology classification was taken from a Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite survey over the area. This was mapped in common with the ASTER data using GIS methodologies.
Experience has shown that certain combinations of spectral bands can discriminate specific types of surface features, and these are often the first ones examined. Although all seven bands can be examined in any combination, it is more convenient to combine three bands to make maps for visual examination. Data from each band, for example the SWIR band, are essentially grayscale data. This grayscale data can be assigned to one of the three RGB colors, with grayscale data from two other bands assigned the other two colors. One common Landsat 7 ETM+ presentation is 742 RGB, where band 7 (SWIR) is represented by red, band 4 (VNIR) by green, and band 2 (VIS green) by blue.
Bands can also be compared by ratio or by difference of their grayscales. Some of the common comparators were not appropriate in the Ghazalat study, because they specifically include bands sensitive to vegetation, and this desert area is dry. Although several of the combinations can discriminate between the sandstone of the plateau and the limestone of the highlands, the combination of a thermal and two SWIR bands had the best differentiation between two different limestone types. This RGB image was sharpened by using a multiband difference that includes responses in two of the visible bands to show texture within the limestone and sandstone. The resulting image highlights the clay pans and details of the layers on the escarpments (Ghazalat Lithology Map).
A different way to classify lithology uses separate criteria specific for each rock type. In the Ghazalat area, several band ratios were evaluated to distinguish two types of limestone, two types of sandstone, and sabkha or clay (Ghazalat Lithology Class Map). This map helped guide a field validation of the data. Traverses through the area by foot and off-road vehicle confirmed the interpretation obtained by remote sensing.
With the lithology and topography determined, the object of the study can be achieved: estimation of risk for a seismic study (Ghazalat Risk Map). One set of risks is associated with access and movement. The steep escarpments and terrain edges limit access to vehicles. The limestone highlands have a rough topography and sharp edges, making maneuvering difficult but not impossible. The clay and sabkha areas also limit access due to the danger of falling through the top crust into soft sediments. In contrast, the sandstone areas, for the most part, have no access limitations.
Other risks are associated with the quality of the seismic signals. The escarpments, including those at formation boundaries, present topographic scattering risks. The rough surface of the limestone increases the risk of point-loading problems with the vibrator pads. The two limestone formations have different levels of this risk, with the western limestone having reduced risk. The soft clay and sabkha have risk of signal attenuation and ringing.
The acoustic velocities in the lithological units can be modeled to estimate source and receiver static corrections. In Ghazalat, this yields a good comparison with the lower resolution estimate obtained from picking the first break in refraction statics. The risks were verified in a shot point in the southern plateau near a mesa (Ghazalat Risk Strip). The shot gather shows the effects of scattering from a mesa edge and from a mineralization boundary, confirming the remote survey.
Ghazalat Lithology
Ghazalat area location and lithologic column. Ghazalat is in the Egyptian Western Desert, bordering on the Qattara Depression (map). The area comprises mesas and tablelands to the south (photograph), with heights to the north. The formations are layers of limestone, sandstone and marl (left).
Ghazalat Topo Map
Topographic map of Ghazalat showing escarpments. A digital elevation map (DEM) shows a part of the Qattara Depression (green, lower right) bounded by a steep and tall escarpment. A broad plateau with mesas (yellow to green) makes up about half the study area, bounded on the north by highlands. An edge-detection algorithm determined the escarpments (black).
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Ghazalat Lithology Map
Ghazalat litho-structural map. A combination of bands from the Landsat 7 satellite provided good discrimination of lithology combined with structure in the arid Ghazalat area. Lithologic discrimination came from a thermal and two SWIR bands, with additional image details overlain from two visible bands.
Ghazalat Lithology Class
Ghazalat lithology classification and ground observations. To create this map, an optimal combination of satellite bands was chosen independently for each lithology class, including two limestone classes, two sandstone classes (combined in this image) and a clay and sabkha class. Mixed colors on this map indicate mixed lithologies within an area. This map was used to plan limited ground traversals, which validated the remotely sensed mapping (photographs).
Ghazalat Risk Maps
Risk maps for Ghazalat area. The logistics risks include access and maneuvering risks for vehicles (top). The sandstone areas are generally low risk, but the highlands are difficult to maneuver in. Large escarpments are impossible for the trucks to access. Risk to data quality, or surface velocity, are also low for the sandstone (bottom). However, risks for point-loading risks in the limestones, attenuation in soft sediments and scattering from escarpments are present.
Ghazalat Risk Strip
Comparison of risk to shot gather. The southern part of the survey had mesas and outcrop features, as shown in the elevation profile and the QuickBird high-resolution satellite image. Extracted maps of several risk classifications are confirmed by distortions in a shot gather that are due to those features.
1.Laake A and Zaghloul A: "Estimation of Static Corrections from Geologic and Remote Sensing Data," _The Leading Edge 27, no. 2 (February 2009): 260-264.
Cutts A and Laake A: "An Analysis of the Near Surface Using Remote Sensing for the Prediction of Logistics and Data Quality Risk," paper presented at the 4th North African/Mediterranean Petroleum and Geosciences Conference & Exhibition, Tunis, Tunisia, March 2--4, 2009.
For information on data quality characterization in arid regions: Laake A, Strobbia C and Cutts A: "Integrated Approach to 3D Near Surface Characterization in Desert Regions," First Break 26 (November 2008): 109--112.
2. The method used is called a Sobel edge detection algorithm. It is often used in north-south and east-west directions, but because of the complicated lobes of the mesas and other features, the eight-direction method used here provided smoother, continuous lines for the escarpments.
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