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Accurate Dip/Strike Measurement using Remotely Sensed Data

PCI Geomatics -

The Perenco Group currently operates over 90 wells and four production gathering stations within a 100 km long zone near Diyarbakir, South East Turkey. Perenco’s export facility exports crude oil to Mediterranean seaports. With daily production of 8 030 barrels of oil equivalent per day (net share), Perenco is the largest foreign oil producer in the country today. Perenco is also actively involved in exploration activities in Turkey, and is committed to increasing reserves through new field discoveries. It is for this reason that the company is increasingly using remotely sensed data in its operations. Through geological and geophysical seismic interpretation and use of orthorectified satellite images, remotely sensed imagery provides insight on the selection of areas to plan seismic surveys for an exploration drilling program as well as aiding in the identification of environmental and operational safety hazards. No other technology can match the capabilities of remote sensing and its necessity in the oil industry.

 

Background
Organizations involved with petroleum exploration have long trusted remote sensing for many areas of oil and gas exploration, yet have traditionally eschewed the method as a means to delineate different types fault zones or folds zone from each other. Lineament analysis of remotely sensed data can give very important information of the tectonic structures.
A lineament can be defined as a linear or curvilinear feature of a surface whose parts align in a straight or slightly curving relationship. Lineaments may be indications of faults or other line weaknesses. Based on research indicating the significance of using surface lineaments for oil and gas exploration, it is possible to conclude that the potential new oil and gas reservoirs, if they exist, will be likely associated with surface lineaments. Therefore, surface lineaments can be employed as a cost-effective tool for delineating preliminary locations for more sophisticated and more expensive geophysical and/or geochemical surveys.
Interpreting surface lineaments using satellite imagery further simplifies the process. In this study for the surface lineament analysis, Geomatica software from PCI Geomatics was used in conjunction with ASTER-Terra satellite images, 45 cm resolution airphotos, and a 2.5 meter DEM from Cartosat data. Dip and strike calculations were performed using PCI’s DIP Module Algorithm.

Gathering the Data
The tectonic map  of  study  area  based  on  field  geology is shown in Figure 1. The actual surface lineament was determined using band rationing with ASTER-Terra imagery. High-resolution 15 meter ASTER imagery was chosen as it yields better results in lineament interpretation compared to Landsat imagery due to improved spatial resolution. ASTER- Terra images Stereoscopic RGB (433) band compositions were used to deploy a visual interpretation technique to perform the lineament mapping. While many different False- Color RGB Composites (FCC) have been used by researchers in the past, this study chose stereoscopic ASTER imagery to create lineament mapping, because a three-dimensional view of the image provides a better solution than FCC composites in both Visible Near Infrared (VNIR) and ShortWave Infrared (SWIR) bands.

Figure 1: The tectonic map of study area with a 45cm resolution airphoto as a base image.

Stereo Imagery Opens up Three Dimensions
ASTER-Terra satellite has three types of spectral bands. In addition to the aforementioned VNIR and SWIR, the satellite also records Thermal Infrared (TIR). Through the VNIR spectrum of ASTER, there are 4 bands with the resolution of 15m while SWIR is 30m and thermal bands have 90m resolution. The three basic bands in the VNIR part of the spectrum have a 15m resolution and an 8-bit unsigned integer data type. This data set also features a near infrared backward-scanning band labeled Band 3B. This is used to create a stereo view of the earth to develop elevation information and should not be used for analysis or classifications. Backward (3b) and Nadir (3n) coverage enable to the users to create stereo image with RGB 3b, 3n, 3n, In other words 433 band combinations in order to see the image in three dimensions. As Figure 2 shows, the main tectonic features are visible.
 
Figure 2: The lineaments map from stereo ASTER imagery in the stereo imagery. After the correlation with stereo image  lineament  map  and  actual  tectonic  map,  some discrepancies are apparent. Therefore, it becomes necessary to use products such as orthophotos for dip and strike analysis to create an accurate tectonic map from this remotely sensed data. Dip and strike, when used together, describe the orientation of a surface in three dimensions. If dip/strike can be measured accurately, the tectonic orientation is easily mapped.

Calculating Dip and Strike Using Geomatica Software
High-resolution imagery and an accurate Digital Elevation Model (DEM) are vital for dip/strike validation. Because satellite data have  lower  resolution  when  compared to airphotos, this study uses a 45cm resolution aerial orthophoto for dip/strike analysis. However, since the aerial photos have no spectral features and no band information, they are only be used for dip/strike analysis. The DEM used to obtain the altitude and terrain information for this study is a Cartosat DEM with 2.5 meter resolution.
Using the DIP Algorithm in PCI Geomatics’ Geomatica software, we can calculate angles of dip and strike for a set of three or more points in three steps. In first step, three vertices are selected (Figure 3). The software builds a plane from these vertices making the calculation of the plane’s dip and strike possible. The second step involves overlaying our DEM and orthophotos for height information because dip/strike analysis needs surface height for each of these three vertices. The last step is to create dip-strike using the DIP algorithm in Geomatica. The Dip angle ranges from 0 degrees for a horizontal plane, to 90 degrees for vertical, Strike direction ranges from 0 to 360 degrees, as defined on a compass. The dip direction is not stored in the software because it is always equal to strike+90 degrees.

Figure 3: Selection of three vertices for strike validation with using orthophoto

 

Results and Conclusions
The field dip/strike measurement is shown Figure 4. The accuracy of the remotely sensed measurements was verified against field data for eight of the dip/strike points; the correlation of which can be seen in Table 1. As indicated in the table, the measurements made from the remotely sensed data are very accurate and closely match the actual field measurements, indicating that the dip/strike module is working very well. As such, the study indicates that using remotely sensed data to calculate accurate dip/strike points as a means to perform lineament analysis is a real possibility and a cost-effective alternative to collecting field measurements.

Figure 4: Remotely sensed and field data dip/strike measurement points.

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