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Generation of heat flow map over a part of the CambayBasin, India using NOAA-AVHRR dataT. J. Majumdar a; P. Nasipuri aa Earth Sciences and Hydrology Division, Marine and Earth Sciences Group,Remote Sensing Applications and Image Processing Area, Space ApplicationsCentre (ISRO), Ahmedabad, India

First Published on: 07 September 2007To cite this Article: Majumdar, T. J. and Nasipuri, P. (2007) 'Generation of heat flowmap over a part of the Cambay Basin, India using NOAA-AVHRR data', GeocartoInternational, 1 - 13To link to this article: DOI: 10.1080/10106040701337584URL: http://dx.doi.org/10.1080/10106040701337584

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Generation of heat flow map over a part of the Cambay Basin,

India using NOAA-AVHRR data

T. J. MAJUMDAR* and P. NASIPURI

Earth Sciences and Hydrology Division, Marine and Earth Sciences Group,

Remote Sensing Applications and Image Processing Area, Space Applications

Centre (ISRO), Ahmedabad 380 015, India

(Received 12 July 2006; in final form 14 March 2007)

Heat flow measurements carried out in the Cambay Basin, India indicate high heatflow values (1.8–2.2 mcal cm72 s71/77–92 mW m72) compared to the normal heat

flow values of approximately (1.4 mcal cm72 s71/58.6 mW m72) for stablecontinental shield areas. This makes the region interesting from a tectonic as wellas a geothermic point of view. The surface heat flow can be computed bymultiplying the geothermal gradient by the rock conductivity. The paper develops a

methodology to determine heat flow using a remote sensing technique. The same isthen measured at a few points in-situ for validation and the methodology is thenextended to a larger (potential oil basin) area using NOAA thermal infrared (IR)

data. The comparison shows encouraging results at match points that may be usefulfor prospective hydrocarbon resources. The heat flow estimation technique usingthe remote sensing approach is, therefore, highly important and can be utilized as

an alternative to conventional heat-flow estimation.

Keywords: Heat flow; Thermal conductivity; Surface temperature; Intrusion;Gravity anomaly; NOAA-AVHRR

1. Introduction

Infrared remote sensing imagery records the surface radiance emitted from theEarth. If instrument calibration, atmospheric and topographic corrections are made,the resulting product represents the surface temperature (Sabins 1997, Majumdarand Mohanty 1998). Surface temperature is the most variable heat source thattransfers heat across the Earth–atmosphere interface. This includes solar radiation(S), surface thermal radiation (R), sensible heat transfer between the ground and theatmosphere (H), surface heat flux (G), and latent heat transfer (L) (Kahle 1977,Majumdar et al. 1983, Majumdar 2003). In a geothermally active region, thecontribution due to terrestrial heat flow from depth plays a major role, and if thecontribution due to other sources could be eliminated, the terrestrial heat flow fromdepth will contribute, in a major way, to the surface temperature.Surface heat flow can be computed by multiplying the geothermal gradient with

rock thermal conductivity. The downward continuation of surface heat flow data to

*Corresponding author. Email: tjmajumdar@sac.isro.gov.in

Geocarto International2007, 1–13, iFirst article

Geocarto InternationalISSN 1010-6049 print/ISSN 1752-0762 online ª 2007 Taylor & Francis

http://www.tandf.co.uk/journalsDOI: 10.1080/10106040701337584

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determine subsurface temperature distributions is a useful method for exploring thesubsurface structures in geothermal areas (Verma and Gupta 1975, Gupta 1981,1982). The calculation of heat flow by conventional methods is laborious and timeconsuming. The Geological Survey of India has drilled a good number of boreholesfor geothermal exploration and the data have been utilized for the computation ofadditional heat flow values (Ravi Shankar 1988).The utilization of thermal IR data for geothermal zoning for regional and

petroleum geology on the basis of satellite IR-thermal survey and for studiesof seismoactive regions has been discussed in detail elsewhere (Gorny et al.1996, Tronin 1996, Nasipuri et al. 2006). Cracknell and Xue (1996) have usedNational Oceanic and Atmospheric Administration (NOAA) Advanced Very HighResolution Radiometer (AVHRR) data and an advanced thermal inertia model forestimation of ground heat flux over an area in France. An attempt was made tocorrelate the silica content in ground water as well as the heat flow to increasethe density of observation and the reliability of a database (Swanberg andMorgan 1978).Estimation of heat flow was attempted using aerial thermal infrared (IR) data by

Majumdar et al. (1983). A calibrated thermal IR image over a part of the CambayBasin has been utilized to determine surface temperature and thereby to detect theheat flow using an empirical approach. Applying the conductive heat flowcontinuation technique, 3-dimensional configuration of the hydrocarbon-bearingreservoir at Shobhasan (Cambay Basin) could be delineated. The heat flowestimation technique using a remote sensing approach is, therefore, highly importantand can be utilized as an alternative to conventional heat-flow estimation.

2. Objectives

The objectives of this study are:

(i) to develop a methodology to determine heat-flow using NOAA thermal IRdata after using a model for surface temperature estimation;

(ii) to apply the heat-flow continuation model to subsurface temperatureestimation over the study area;

(iii) to validate the results with the available in situ and borehole measurements.

3. Data sources and area of study

NOAA-14 (date of pass: 14 January 2001) passes at around 1400 hours, ISTlocal time. NOAA AVHRR data have been widely used for environmental researchat regional and global scales. NOAA AVHRR Local Area Coverage (LAC) datawith a spatial resolution of 1.1 km at nadir and a radiometric of 10 bits have beenutilized to generate heat flow images over the Cambay Basin. The level lb datacontain raw AVHRR spectral data as well as calibration coefficients, solar zenithangles, earth location, and other auxiliary data (Di and Rundquist 1994, NOAA1990).The Cambay Basin, Gujarat, India (22–248 N, 72.5–73.258 E) is an ideal site for

this study. Besides being geothermally active, it contains several oilfields. The sensorcalibration curve is utilized to obtain the surface temperature. The surface andsubsurface temperatures were measured at limited ground control points and a few

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bore holes respectively (subsurface temperature data over boreholes received fromOil and Natural Gas Corporation, Dehradun). The value of rock thermalconductivity is assumed to be 0.005 cal cm71 s71 8C71 (2.09 W m71 K71). Over5 km thick tertiary sediments (clay stone, sandy siltstone and shale) are mainlypresent in this area (Cambay Basin). Accordingly, a generalized value of0.005 cal cm71 s71 8C71 (2.09 W m71 K71) has been chosen as per availablelithologs in the area (Sabins 1997).

3.1 Geology of Gujarat

Geologically, Gujarat represents a wide spectrum of rock types of different ages. Thegeology of Gujarat consists of three distinct physiographic units (Merh 1995,Nasipuri et al. 2005). The various maps used for this study include geological/tectonic maps over the study area.

3.1.1 Mainland Gujarat. The geological evolution of the northern and eastern partsof Gujarat has been controlled by the Pre-Cambrian orogenies. A major part of themainland falls within the Cambay and Narmada graben and eastern and northernPre-Cambrian rock marks the boundary. The rock of the mainland shows an agerange from Proterozoic to recent. A striking feature of mainland stratigraphy is thetotal absence of Paleozoic rock and the development of Mesozoic rock only. Thetopmost deposit is continental sediments deposited in fluvio-marine, fluvial andaeolian environments.

3.1.2 Saurashtra peninsula. The peninsula of Saurashtra is a horst bordered byfractures related to three intersecting rift trends, viz. the Delhi trend (NE-SW), theNarmada trend (ENE-WSW) and the Dharwar trend (NNW-SSE) (Biswas 1987).The Saurashtra region contains only Mesozoic and Cenozoic rocks and stratigra-phically the sequence begins with the Cretaceous, followed upwards by DeccanVolcanics, Tertiary and Quaternary deposits.

3.1.3 Kutch Region. This is an important site of Mesozoic and Cenozoicsedimentation. Unbroken rich fossiliferous sequences from Jurassic upwards arevery well preserved.

3.2 Geology of the Cambay Basin

The Cambay Basin is a marginal aulacogen basin situated in the western part ofIndia. It is an intracratonic graben covered by alluvium. A thick sequence of tertiarysediments occurs beneath the alluvial cover over the basement of the Deccan trapbasalt. The basin extends offshore to the south as a narrow graben parallel with thecoast between Bombay High and the mainland (Raju 1968, Biswas 1987). Besidesbeing geothermally active, this is a proven petroliferous basin covering an area ofabout 53,500 km2. More than 90 oil and gas fields have been discovered, with twofields, Ankleshwar and Gandhar, which are of giant size. Over 5 km thick tertiarysediments (clay stone, sandy siltstone and shale) are present. The total predictedhydrocarbon resources are of the order of 2050 MMt and established in-placereserves are of the order of 1188 MMt. Structural, tilted fault closure and strati-structural playas in tertiary sediments are the main exploration targets (figure 1).

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The Cambay Basin is composite and developed sequentially from north to southduring India’s northwards drifting after the break up of Gondwanaland. Thedevelopment of three major rift basins in the western margin, namely Kutch,Cambay and Narmada rift basins, seems to be related to the evolution of the westernmargin of India in three stages. The stages are (1) separation of Africa from India inearly Jurassic (Besse and Courtillot 1988), (2) separation of Madagascar from Indiacaused by Marion hot spot during middle Cretaceous (Morgan 1981), (3) break up ofthe Seychelles from India caused by the Reunion hot spot during late Cretaceous,which gave rise to Deccan Trap basalts (McKenzie and Slater 1971).The deepest part of the basin is recorded between the Narmada and Mahisagar

rivers, where more than 5000 m of sediments have been deposited. Initially it wasbelieved that the basin was being divided into two parts by an east–west-trending

Figure 1. Location of the Cambay Basin, Gujarat, India.

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fault along the Narmada River. However, recent data indicate that apart from thatfault, there are other faults in that basin which have divided the basin into variousblocks (Mitra et al. 1984).

4. Methodology

4.1 Calibration of AVHRR data

AVHRR thermal data (channels 3, 4 and 5) may be converted to temperature andthe visible and near infrared data (channels 1 and 2) may be converted to reflectancebased on the look-up table (LUT) given in the NOAA-AVHRR CD. Accordingly,channel 4 and 5 data were converted to temperatures using those LUTs.

4.2 Retrieval of brightness temperature

The retrieval of brightness temperature from the thermal bands 4 and 5 of NOAA 14AVHRR images was done by using inverse Planck’s equation, which is as follows(Saraf et al. 1995):

T ¼ c2= l ln 1þ elc1l�5=EðlÞ

� �� �� �ð1Þ

where T is the temperature (K) for the energy value E (l), c1 and c2 are constants,E (l) is the radiance energy value in the thermal IR band, e is the emissivity.

4.3 Retrieval of land surface temperature

Terrestrial surface temperature measurements by sensors are attenuated by theEarth’s atmosphere by decreasing the observed brightness temperature (due to watervapour) as received by the sensor. In a non-cloudy region of interest, the majorperturbation factor is due to the existence of atmospheric water vapour and differenttechniques exist for its evaluation (Price 1984, Becker 1987, Zhirong and McDonnell1988, Majumdar and Bhattacharya 1988, Kealy and Hook 1993, Prata et al. 1995).Among the existing techniques, the split-window channel method is the mostpopular for calculating the surface temperature over oceans, as the case is simplifieddue to the homogeneity of a pixel (Prabhakara et al. 1974, Singh 1984). However, thesituation becomes complex over land due to the following reasons (i) land surfacetemperature is generally not homogeneous within a pixel as in the case of the ocean,(ii) the difference between land surface temperature and air temperature near thesurface is larger for land surfaces than for the sea, and (iii) land surface emissivitiesmay be quite different from unity and spectrally variable, which is not the case forsea (Becker 1987, Cooper and Asrar 1988, Vidal 1991, Coll et al. 1994, Majumdarand Mohanty 1998).AVHRR channels 4 and 5 are designed to exploit an atmospheric window in the

thermal region of the electromagnetic spectrum, where attenuation is relativelysmall, which, however, introduces significant error in AVHRR-sensed surfacetemperature. To eliminate the atmospheric effects due to water vapour, Price’s model(Price 1984, Cooper and Asrar 1988) has been used:

Tc ¼ ðch 4Þ þ 3:33 ðch4� ch5ÞðKÞ ð2Þ

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where Tc is the atmosphere corrected surface temperature, ch4 is the calibratedsurface temperature from channel 4, ch5 is the calibrated surface temperature fromchannel 5. For the 10–12 mm spectral region spectral emissivity (e) values areassumed to be varying within 0.95–0.99, which is the case for most of the land classes(Taylor 1979, Price 1983, Majumdar and Bhattacharya 1988).

4.4 Calculation of subsurface temperature and heat flow

The major problem in the calculation of subsurface temperature distribution is thespatial diffusion of heat. Since the flow of heat is not restricted to vertical directiononly, the estimation of subsurface temperature by extrapolation of the surfacegeothermal gradient is erroneous. The correct solution of this problem is downwardsor source-wards continuation of heat, which accounts for the spreading of heat inall directions. Such a heat flow continuation technique has been developed byCarslaw and Jaeger (1959), Brott et al. (1981) and others. The general approach to theproblem, as described by Brott et al. (1981) and used in the present text is given below.To obtain a uniform surface temperature image, sources must be considered. The

heat flow (Qij) of a point (i,j) on a plane is represented as

Qij ¼ GijK0 ð3Þ

Where Gij is the geothermal gradient at that point and K is the rock thermalconductivity. The strength (Sij) of a continuous and constant heat generation pointsource in a homogenous isotropic medium, in which no heat is generated between thesource and the surface and the heat transfer mechanism is by conduction alone, canbe calculated by

Sij ¼ Qij=4pK0 ð4Þ

Where K0 ¼ (K/rC) is the diffusivity, r is the density of the material and C the specificheat.Once the source term is calculated, the subsurface temperature Tij at the point Pij

at a vertical depth Z can be expressed as (Brott et al. 1981)

Tij ¼Xn

k¼1

Xm

l¼1Sijkl ðDijkl �D0ijklÞ þ TSij þ ðGijZÞ ð5Þ

where D and D0 are the steady state distance terms, which are expressed as

D ¼ 1=R and D0 ¼ 1=R0 ð6Þ

where R is the distance from the source to the field point and R0 is the distance fromthe image to the field point. TSij is the surface temperature at the point (i, j).Considering a constant temperature for a particular layer e.g. a hydrocarbon-bearingreservoir, the depth to the formation can be computed with the help of equation (5).The Cambay basin is an ideal area for this study. Besides being geothermally

active, it contains several active oil fields. It is expected that the hydrocarbon-bearingreservoir will maintain two different isothermal patterns, both on the top andbottom of the structure, which may influence the heat flow patterns in the region

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(Majumdar et al. 1983). A test site around Shobhasan covering an area of 40 km2

was selected for this study. The aerial thermal IR (8.5–12.5 mm) data were acquired.The sensor calibration curve is utilized to obtain the surface temperatures. Thesurface and subsurface temperatures were measured at limited ground control pointsand from a few drill wells, respectively. The test area is divided into grids, each0.25 km2 in size. Thus the heat flow data comprise a set of spatially distributed fieldstrength values on the surface generated by an array of point sources representingeach grid. The value of rock thermal conductivity (K) and diffusivity (K0 ¼K/rC)(r is the density and C is the specific heat of the material) are assumed to be 0.005 calcm71 8C s (2.09 W m71 K71) and 0.01 cm2 s71 (100 m2 s71), respectively on thebasis of available lithologs of the area (Sabins 1997). From the available temperaturelogs, a calibration curve was made for surface temperature as a function ofgeothermal gradient (figure 2) (Majumdar et al. 1983).Initially a set of points for which bore hole data were available were chosen to

make a calibration curve with the corresponding surface temperatures and thegeothermal gradients. Later, a model using the heat flow continuation technique(Brott et al. 1981) was used to validate the subsurface temperatures using the avai-lable lithologs, which showed satisfactory results (Majumdar et al. 1983). The geo-thermal gradient image of Cambay Basin (figure 3) was then generated using thecalibration curve shown in figure 2.

5. Results and discussion

The overall geothermal gradient values over the Cambay Basin vary from 308Ckm71 to 408C km71. Assuming the rock conductivity 0.005 cal cm71 8C71 s71

(2.09 W m71 K71) based on the lithology of the area concerned, the heat flow map(figure 4) of the area is generated using equation (3). The heat flow varies from1.7 mcal cm72 s71 to 1.99 mcal cm72 s71 (75–93 mW m72) with a mean value of

Figure 2. Calibration curve of geothermal gradient and surface temperature.

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1.844 mcal cm72 s71 (77 mW m72). The observed value of heat flow in the Cambaybasin is recorded as 1.8+ 0.4 mcal cm72 s71 (77 mW m72) (Verma and Gupta1975, Gupta 1981, Majumdar et al. 1983, Mitra et al. 1984).The heat flow image of the Cambay Basin shows considerably higher values than

the stable continental crust (Verma et al. 1968, Verma and Gupta 1975). On thisbasis it appears that Cambay oil field is the region for high heat flow. There is nogranitic body nearby, which would suggest higher radioactivity of the underlyingcrust as the possible cause. Another interesting and conspicuous feature of theCambay basin is its high gravity field. The residual anomaly is about þ37 mgal nearCambay and it decreases in amplitude towards the North. According to Verma et al.

Figure 3. Geothermal gradient map over a part of the Cambay Basin, Gujarat, India.

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(1968) and Gupta (1981) this gravity high is due to the presence of an intrusive bodyin the Earth’s crust at a depth of about 10 km. The presence of such an intrusivebody can explain the high heat flow as well as gravity high in the basin, which mighthave been caused by the frictional heating of the intrusive body.The study of the hydrocarbon accumulation indicates that the light oil is found in

Shobhasan, Ankleshwar, Broach areas, whereas in those areas where the heat flow iscomparatively high, the percentage of gas gradually increased (The Cambay GasField) (Verma and Gupta 1975, Majumdar et al. 1983, Mitra et al. 1984, RaviShankar 1988). In this way, the heat flow map has been prepared from thermal IRimages after making the necessary corrections and the obtained heat flow valuescorrespond well with the ‘Field Estimated Heat Flow’ (Ravi Shankar 1988). A

Figure 4. Heat flow map over a part of the Cambay Basin, Gujarat, India.

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comparison has been made between the ‘Remotely Sensed Heat Flow’ and the ‘FieldEstimated Heat Flow’ as shown in table 1.In-situ heat flow values have been taken from Ravi Shankar (1988) whereas the

NOAA data were collected in 2001. However, it has to be noted that the generalizedheat flow values do not change so frequently and may differ with geological age. It isexpected to remain constant within this time gap of approximately 15 years(Ravi Shankar 1988).

6. Conclusions

Heat flow estimation over a geothermally active region e.g. the Cambay Basin,Gujarat is highly important due to the presence of a number of active oil fields in thisregion. An empirical approach has been used here to extend the NOAA-AVHRRderived surface temperature data to the corresponding geothermal gradient and thenheat flow estimation in this region. The heat flow values thus obtained match wellwith the field observed heat flow values at certain points and also match well with thegeneral trend of heat flow in this geothermally active region. The Cambay andNawagaon regions are considered to be high heat flow regions and geothermallymore active. NOAA derived surface heat flow, as obtained using the present model,also shows similar results. The presence of an intrusive body at around 10 km depthmay explain the cause of high heat flow as well as gravity high in the basin. Ifestimated properly, remote-sensing based heat flow estimation can be a boon forsimilar measurements due to its savings in time and effort, which are required forground truth estimates.

Acknowledgements

The authors wish to thank the anonymous referees for their critical comments for theimprovement of the manuscript. They are also thankful to Dr R. R. Navalgund,Director, Space Applications Centre (SAC), Dr K. L. Majumder, Ex-Deputy.Director, Remote Sensing Applications and Image Processing Area (RESIPA)/SACand Dr Ajai, Group Director, Marine and Earth Sciences Group (MESG) for theirkeen interest in this activity. Thanks are also due to Shri R. Bhattacharyya, SeniorResearch Fellow, Earth Sciences and Hydrology Division (ESHD)/MESG/RESIPA/SAC for his help. Geothermal data obtained from Keshava Deva Malaviya Instituteof Petroleum Exploration (KDMIPE), Oil and Natural Gas Corporation (ONGC)gratefully acknowledged.

Table 1. Comparison of heat flow values in selected locations using two different methods.

Heat flow values measuredconventionally

(Ravi Shankar 1988)

Heat flow values estimated from heatflow model with NOAA-14 data

(14 January 2001)Area mW m72 mcal cm72 s71 (mcal cm72 s71)

Cambay 93 2.22 1.89Nawagaon 82 1.95 1.75Sanand 75 1.79 1.71Kalol 78 1.84 1.75Mehsana 80 1.91 1.8

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