Remote sensing for petroleum exploration,Part 1: Overview of imaging systems

FLOYD F. SABINS, Remote Sensing Enterprises, Fullerton, California

his paper, the first of two thatsummarize remote sensing as ap-plied to petroleum exploration, pro-vides an overview of the science andthe computer techniques used toprocess the data. The second (to bepublished in TLE’s May issue) willdescribe successful oil-explorationprojects that employed remote-sens-ing technology. The examples arefrom projects by colleagues and my-

self at Chevron, from which I retiredin 1992.

Remote sensing has several ap-plications to geophysical explorationof onshore regions. Images are inter-preted to produce geologic mapsthat show structural trends and po-tential prospects which are, in turn,used to plan an efficient seismic pro-gram. Furthermore, if an area lacks areliable base map, one can be readi-ly generated from remote-sensingdata, as can maps showing accessand trafficability which can also im-prove the efficiency of field opera-tions. (When Lee Lawyer, a formerSEG President, was chief geophysi-cist of Chevron Overseas Petroleum,he insisted that any onshore seismicsurvey be preceded by a remote-sensing interpretation.) Landsat im-ages have also been employed inshallow offshore areas to identify un-charted reefs and other hazards toseismic surveys.

Remote sensing is defined as thescience of acquiring, processing, and in-terpreting images from satellites and air-craft that record the interaction betweenmatter and electromagnetic energy. Re-mote-sensing images of the earth areacquired in three wavelength inter-vals, or regions, of the electromag-netic spectrum. The visible regionranges from 0.4 to 0.7 µm and is di-vided into the blue, green, and redbands. The infrared (IR) regionranges from 0.7 to 30 µm and is di-vided into the reflected IR and ther-

mal IR portions. The reflected IR por-tion ranges from 0.7 to 3.0 µm; theenergy is predominantly reflectedsunlight at wavelengths longer thanvisible light. The Landsat and SPOTsatellite systems acquire valuable im-ages in the visible and reflected IR re-gions. The thermal IR portion rangesfrom 3.0 to 15.0 µm; the energy is ra-diant, or heat, energy. Thermal IRimages have considerable potentialfor exploration in arid and semiaridterrains; however, the method hasbeen underutilized in recent yearslargely owing to the lack of suitableimages.

Images in the visible, reflected IRand thermal IR are acquired in thepassive mode by systems that simplyrecord the available energy that isreflected or radiated from the earth.The microwave region ranges from0.1 to 30 cm; images for explorationare primarily acquired in the activemode called radar. This paper focus-es on three systems: Landsat The-matic Mapper and SPOT panchro-matic images in the visible andreflected IR regions, and aircraftradar images.

Landsat Thematic Mapper images.Landsat is an unmanned satellitethat orbits the earth in a sun-syn-chronous pattern at an altitude of705 km. The two second-generationsatellites carry the thematic mapper(TM) system. TM is a multispectralsystem which records seven separate

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Figure 1. Reflectance spectra ofvegetation and sedimentary rocks,showing spectral ranges of Land-sat TM and SPOT systems. Allfigures in Part 1 are from Sabins(1997).

Figure 2. Landsat TM bands. (a) = 2 (green), (b) = 4, and (c) = 7 (both reflected IR). (d) = geologic features nearThermopolis, Wyoming, as interpreted from Figure 3.

images, or bands, for each scene.Figure 1 shows wavelength ranges ofthe three visible bands (1, 2, 3) andthree reflected IR bands (4, 5, 7).Band 6 records thermal IR energybut is rarely used for exploration.The reflectance spectra of commonsedimentary rocks and vegetation inFigure 1 provide insights for select-ing the optimum TM bands for in-terpretation. The spectra of the dif-ferent rocks are very similar in thevisible bands but have major dis-tinctions in the reflected IR bands;therefore, TM bands 4, 5, and 7 areespecially useful for mapping differ-ent rock types.

TM images are acquired by across-track scanner with an oscillat-ing mirror that sweeps across the ter-rain normal to the satellite groundtrack. A spectrometer separates thereflected sunlight into the six spectralbands. The image data are teleme-tered to ground receiving stations viathe tracking and data relay satellites(TDRSS). A TM image covers 170 �185 km2 of terrain with a spatial res-olution of 30 m. The digital data arestored in a raster format. An individ-ual band consists of 5667 scan lines,each of which contains 6167 pictureelements (pixels) for a total of almost35 million pixels. A pixel represents a30 � 30 m ground-resolution cell andrecords the intensity of reflected en-ergy on an eight-bit scale, rangingfrom 0 (minimum reflectance) to 255(maximum reflectance).

Any three bands may be mergedin any combination of blue, green,and red to produce a color compos-ite image. There are 120 possiblecolor combinations, but theory andexperience show that a small numberof combinations are suitable for mostregions and applications. Figure 2shows TM bands 2, 4, 7 for a smallsubarea that includes the town ofThermopolis in the Bighorn Basin ofWyoming. These bands are general-ly optimum for arid and semiarid ter-rain, such as central Wyoming. Fig-ure 3 is a color composite of bands 2,4, 7 merged in blue, green, and red.Figure 2d is a map showing major ge-ologic features interpreted from thissmall-scale color image. Four anti-clines are seen in the image. The Lit-tle Sand Draw and Gebo anticlinesare oil fields that were discoveredlong before the launch of Landsat.Images of existing oil fields are valu-able examples for interpreting im-ages of frontier regions. Detailedmaps at scales as large as 1:50 000 are

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Figure 4. Terrain returns and image signatures for a pulse of radar energy.

Figure 3. Color composite image of TM bands 2, 4, and 7 combined inblue, green, and red. Thermopolis, Wyoming subarea.

interpreted from larger-scale versionsof TM images. Part 2 of this articlewill describe how TM images con-tributed to oil discoveries in the Cen-tral Arabian Arch.

Landsat was launched by NASAand is operated by Space ImagingEOSAT. Images, in digital or hard-copy format, are sold by Space Imag-ing EOSAT, 4300 Forbes Boulevard,Lanham, Maryland 20706 (http://origin.eosat.com/) and by the USGSEROS Data Center, Sioux Falls, SouthDakota 57198 (http://edcwww.er.usgs.gov/).

SPOT images. The SPOT unmannedsatellite orbits the earth in a sun-syn-chronous pattern at an altitude of832 km. Images are acquired byalong-track scanners in which lineararrays of detectors are aligned nor-mal to the ground track. As the satel-lite moves forward, each detectorsweeps a narrow strip of terrain par-allel with the track. SPOT imagescover 60 � 60 km2 of terrain and areacquired in two modes: SPOTpanchromatic (pan) and SPOT mul-tispectral (XS). Figure 1 shows thespectral ranges of these images. TheSPOT pan system records a singleimage in the spectral band 0.51 to0.73 µm with a spatial resolution of10 m. The SPOT XS system recordsthree images in the green, red, andreflected IR bands, with a spatial res-olution of 20 m. The XS system doesnot acquire images in the wave-length intervals of TM bands 5 and 7.The SPOT scanner may be tilted toacquire images up to 475 km to theeast or west of the ground track,which provides two advantages:

• An area may be imaged up to 11times during the 26-day repeatcycle, depending upon its lati-tude.

• Two images of an area acquiredfrom different orbit paths haveparallax which enables them tobe viewed stereoscopically. SPOT

stereo images have been used toprepare detailed contour mapsof exploration concessions thatlack conventional topographicmaps.The regional coverage and spa-

tial resolution of TM images are wellsuited for regional mapping. Thehigher spatial resolution and stereocapability of SPOT pan images arewell suited for detailed local map-ping. SPOT images and data are soldby SPOT Image Corporation, 1897Preston White Drive, Reston, Vir-ginia 22091-4368 (http://www.spot.com/).

Radar images. Radar is an activeform of remote sensing that is showndiagrammatically in Figure 4. Pulsesof microwave energy, at wavelengthsof a few centimeters to a few tens ofcentimeters, are directed to the ter-rain from an antenna carried on anaircraft or satellite. Energy is direct-ed downward toward the side of theground track. The angle between thehorizon and the radar beam is calledthe depression angle. Each radarpulse “illuminates” a narrow strip,or scan line, of terrain normal to thetrack. Figure 4 shows a single scanline. Figure 5b is a typical radarimage which consists of many scanlines. The incident energy interactswith the terrain, and portions are re-turned to the radar system whichrecords the data. Three characteris-tics of terrain determine the intensi-ty of the radar return:

• Dielectric constant, which is large-ly a function of moisture content.

• Surface roughness at a scale ofcentimeters. Smooth surfaces,such as calm water, have dark sig-natures. Rough surfaces, such asforests and coarse gravel, havebright signatures.

• Topography. Figure 4 shows thatslopes facing toward the radar an-tenna have bright signatures,called highlights. Slopes facing

away from the antenna have darksignatures, called shadows. Thisattribute of radar is most impor-tant for geologic interpretation.

Figure 4 shows the analog signalthat is received for the scan line. Thesignal is digitized and recorded forlater processing and playback to pro-duce images. Modern radar imagesare acquired in the synthetic aperture(SAR) mode that achieves high spa-tial resolution, even at satellite alti-tudes. Topographic maps are pro-duced from repeated images usingthe process called interferometerSAR (IFSAR).

Radar images have two majoradvantages over visible and reflect-ed IR images, such as Landsat andSPOT. Because radar is an active sys-tem that provides its own source ofenergy, images can be acquired dayor night and through dense clouds orfog. Aircraft radar images are typi-cally acquired with a low depressionangle of 20° or less (Figure 4) whichcauses strong highlights and shad-ows from topographic features thatmay express geologic structures.

Figure 5 compares an aircraftradar image with a Landsat TMimage of the Mapia anticline in IrianJaya, Indonesia. The TM image wasacquired with a sun elevation of 45°above the horizon and lacks stronghighlights and shadows. The aircraftradar image was acquired with a de-pression angle of 17°. The resultinghighlights and shadows enhance thedip slopes in the upper portion of theradar image and the flanks of the an-ticline in the lower portion. Figure 6is a geologic interpretation of theimage. In addition to structure, dif-ferent rock types are also recognizedby their distinctive signatures. Fandeposits along the upper margin ofthe image (Figure 5b) form broadslopes with no stratification. Theupper member of the Buru Forma-tion (Tbu in Figure 6) has a distinc-tive ledge-and-slope topography

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Figure 5. Comparison of (a) Landsat and (b) aircraft radar images over Mapia anticline, Irian Jaya, Indonesia.

a) b)

caused by the interbedded resistantsandstone and nonresistant shale.The nonresistant shale of the lowermember of the Buru Formation (Tbl)forms a broad valley. The NewGuinea Limestone (Tn) forms thebroad arch of the Mapia anticline.The uneroded nature of the lime-stone indicates that it has been ex-posed relatively recently. In humidregions, prolonged erosion of lime-stones produces karst topographywith a distinctive pitted signature.The radar image is clearly prefer-able to the TM image for geologicinterpretation. This enhancement ofgeologic features misled some earlyinterpreters to believe that radar en-ergy penetrated a forest canopy andimaged the underlying surface.Both radar theory and images showthat radar signatures are largely theresult of interactions with the upperfew centimeters of vegetation. Part2 will describe how radar imagescontributed to oil discoveries in therain forest terrain of Papua NewGuinea.

NASA has conducted three radarmissions of earth from the SpaceShuttle, called Shuttle Imaging Radar(SIR). Images of the eastern Sahara inEgypt and Sudan showed that theradar energy penetrated up to sever-al meters of sand and imaged the un-derlying bedrock. Field and labora-tory investigations showed that thispenetration occurred because of thehyperarid environment. Only a fewadditional examples of sand pene-

tration have been documented. Otherdesert sands apparently contain suf-ficient moisture to attenuate the radarenergy. Information on the SIR-C im-ages acquired in 1994 is available onthe EROS Data Center Web site(http://edcwww.cr.usgs.gov/lan-dacc/sir-c/sir-c.html).

Several unmanned satellites areacquiring radar images. The JapanEarth Resources (JERS) and the Eu-ropean Remote Sensing (ERS) satel-lites acquire images at a steep de-pression angle that results ingeometric distortion called layover.These images are not suitable for ge-ologic interpretations of terrain withmoderate or high relief. The Canadi-an Radarsat satellite acquires imagesat a variety of depression angles andformats, several of which are suitablefor geologic interpretation. Imagesand information are available fromRadarsat International 3851 ShellRoad, Richmond, British ColumbiaV6X 2W2 (http://www.rsi.ca).

Digital image processing. Except forconventional aerial photographs, allremote-sensing images are acquiredin digital format and are computerprocessed to produce images for in-terpretation. This paper will simplydescribe the three functional cate-gories of image processing and listrepresentative processing routines.• Image restoration compensates fordata errors, noise, and geometric dis-tortions introduced during the scan-ning, recording, and playback oper-

ations. This includes restoring linedropouts; restoring periodic linestriping; restoring line offsets; filter-ing random noise; correcting for at-mospheric scattering; and correctinggeometric distortions.• Image enhancement alters the visu-al impact that the image has on theinterpreter in a fashion that improvesthe information content. This in-cludes contrast enhancement; densi-ty slicing; edge enhancement; mak-ing digital mosaics; intensity, hue,and saturation transformations;merging data sets; and syntheticstereo images.• Information extraction utilizes thedecision-making capability of thecomputer to recognize and classifypixels on the basis of their digitalsignatures. The major results areprincipal-component images; ratioimages; multispectral classification;and change-detection images.

These routines are described andillustrated in the book by Sabins (see“Suggestions for further reading”).

Summary. Landsat TM, SPOT, andradar images are covered in this re-view because the images are readilyavailable and are well suited for oilexploration. The data are primarilyavailable in digital format and re-quire specialized computer process-ing and reproduction to produce im-ages suitable for interpretation.Unless a user is familiar with imageprocessing, it is advisable to employa contract organization to providethese services.

Suggestions for further reading. Abasic reference is Remote Sensing —Principles and Interpretation, ThirdEdition, by Sabins (W. H. Freeman,1997). The American Society forPhotogrammetry and Remote Sens-ing publishes the Manual of RemoteSensing. The third edition is in pressand should be available soon. TheInternet is an excellent source of im-ages and information. The Web’sVirtual Library: Remote Sensing site(http://www.vtt.fi/aut/ava/rs/virtual/) provides extensive links to in-formation sources.

Corresponding author: Floyd Sabins, phone562-694-7370; email ffsabins@usa.net

Authors interested in submitting articles tothe Geologic Column should contact RayThomasson (303-436-1930) or Lee Lawyer(713-531-5347) who are coordinating andediting this series.

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Figure 6. Geologic interpretation of radar image of Mapia anticline, IrianJaya.

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