T. J. Majumdar

On the utilization of ERS-1 altimeter data for offshore oil exploration

In this paper, methods for the generation of residual and prospecting geoids and free-air gravity anomaly using satellite altimeter data are developed. Maps of residual geoid, gravity anomaly, and their spectral components generated over Indian offshore using ERS-1 altimeter data are presented and interpreted. A number of known megastructures over the study area, for example, Bombay High, Saurastra platform, 90 east ridge, etc., are interpreted successfully from these maps. Some of the anomalous zones (the basins near Mangalore and off Bombay High in the western offshore and Palar basin off Madras coast in the eastern offshore) have been identified as potential sites for occurrences of hydrocarbon-bearing structures, for which detailed ship-borne geophysical surveys have been commissioned by the Oil & Natural Gas Corporation (ONGC), Dehradun, India.

Geological appraisal over the Singhbhum-Orissa Craton, India using GOCE, EIGEN6-C2 and in situ gravity data

a b s t r a c t The gravity field and derivatives generated with the high resolution EIGEN-6C2 gravity model which includes satellite gravity data of GOCE (Gravity field and steady-state Ocean Circulation Explorer) has been utilized for geological appraisal of the Singhbhum-Orissa Craton, India. The GOCE only field gravity data and in situ gravity data of the same area have been utilized for comparative assessment to validate the results derived by EIGEN-6C2 gravity data. The GOCE and EIGEN-6C2 Bouguer gravity data have been generated from GOCE and EIGEN-6C2 Free-air gravity data, respectively, after removing topography effect. The result shows that correlation coefficient and covariance between the Bouguer gravity anomaly distribution of in situ and EIGEN-6C2 data of the entire study area are 0.68 and 93.9 mgal2, respectively. The GOCE field compares well to the terrestrial derivative fields in the long-wavelength part of the signal. Further, EIGEN-6C2 and in situ Bouguer gravity data have been analyzed using the 1st and 2nd Vertical Derivatives, Analytical Signal and Tilt Derivative mapping techniques. Published geological and structural maps of the area have been overlapped over different derivative maps and the analytical signal map to analyze the correlation with the subsurface geology and geological structures of the area. Major distinct geological signatures, on different derivative maps and analytical signal map, are correlated well with the existing geological map. The TDR derived from the EIGEN-6C2 Bouguer anomaly has been used to map geologic contacts. The source boundaries and depths are determined from the zero contours, and the half distance between ±/4 contours or the distance between zero and +/4 or −/4 contour of TDR, respectively. The gravity data generated from EIGEN-6C2 model provides sufficient resolution for understanding of the geological setting of the Singhbhum-Orissa Craton.

Usage of ERS SAR data over the Singhbhum Shear Zone, India for structural mapping and tectonic studies

The extraction of lineaments and anomalous patterns in the Singhbhum Shear Zone, Jharkhand, India, has multifaceted applications for mineral exploration as well as for geological interpretation of neotectonic movements. ERS-1 SAR data are very useful for such applications because of their structural information content. A comparative study has been attempted with ERS, Landsat and IRS images for the interpretation of various geological structures over the Singhbhum Shear Zone. The Rose diagram generated from this study has shown major trends that matched well with the geological map of the area and the associated tectonic boundary as well as with the results obtained from ground based studies.

Using artificial neural networks for synthetic surface fitting and the classification of remotely sensed data

Abstract The potential of neural networks in multidimensional interpolation was explored using a multilayer perception for fitting surfaces to a synthetic topographic dataset. Density-sliced and shaded relief images generated through this neural network-based surface-fitting scheme were compared with those generated by conventional approaches, eg, Akimas quintic polynomial fit and inverse square method [Akima, 1978]. Compared with the conventional approaches, the neural network approach was found to better represent the nonlinearity in the synthetic dataset. This paper also presents a method for classifying remotely sensed data, using an artificial neural network (ANN) approach. The ANN used was a multilayer perception trained through the generalized delta learning rule. The software package was completely generalized in nature and could deal with any number of input units (spectral bands), output units (feature classes) and hidden layers. Different numbers of hidden neurons could also be considered in various hidden layers. The software package was also used for classifying IRS-1A LISS-1 images.

Utilization of high-resolution EGM2008 gravity data for geological exploration over the Singhbhum-Orissa Craton, India

High-resolution EIGEN6C4 and EGM2008 Bouguer gravity data of 2190 degree spherical harmonic over the Singhbhum-Orissa Craton, India, have been generated from the International Centre for Global Earth Models. The Bouguer gravity anomaly difference maps of (i) in situ and EIGEN6C4, (ii) in situ and EGM2008 and iii) EIGEN6C4 and EGM2008 of the study area are compared. It reveals that EIGEN6C4 has lesser systematic error than EGM2008. However, from different profile plots of Bouguer gravity, east–west horizontal derivative and north–south horizontal derivative anomalies of the in situ, EIGEN6C4 and EGM2008, it is observed that most of the signatures of lithounits and geological structural elements are delineated very well by EGM2008 and match 94–98% with those of EIGEN6C4. Further, the Bouguer gravity, east–west horizontal derivative and north–south horizontal derivative anomalies of EGM2008 data over the study area have been used effectively for identifying various lithounits and geological structural elements.

Generation of emissivity and land surface temperature maps using MODIS TIR data for lithological mapping over the Singhbhum-Orissa Craton

The present study was undertaken with four fold objectives, namely, (i) to estimate land surface temperature using MODIS TIR data; (ii) to calculate relative emissivities from MODIS TIR data; (iii) to identify various lithologies based on relative emissivity and land surface temperature estimation; and finally, (iv) to carry out comparative assessment analysis between the prepared lithological map and the published lithological map. The land surface temperatures for different pixels were estimated using two methods, viz., Reference Channel and Emissivity Normalization; whereas, relative emissivities were calculated by applying three methods, viz., Reference Channel, Emissivity Normalization and Alpha Residual. Lithological maps were subsequently prepared based on the estimated land surface temperatures and relative emissivity values. The present study shows that the Emissivity Normalization method gives the best results for land surface temperature estimation and also for lithological discrimination based on emissivity estimation. Twenty-four lithounits demarcated by the present study match with those of the published map, while four lithounits of the published map could not be identified in the present study. On the other hand, six additional unclassified lithounits could be demarcated in the present study, which need to be crosschecked by field study.

Study of spectral signatures for exploration of Bauxite ore deposits in Panchpatmali, India

Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique.

Utilization of Landsat ETM+ data for mineral-occurrences mapping over Dalma and Dhanjori, Jharkhand, India: an Advanced Spectral Analysis approach

The Advanced Spectral Analysis (ASA) technique, one of the most advanced remote-sensing tools, has been used as a possible means of identifying mineral occurrences over Dalma and Dhanjori. The ASA technique is a sixfold tool, which includes the continuous processes of (1) the reflectance calibration of Landsat Enhanced Thematic Mapper (ETM+) images of the study area, (2) the generation of minimum noise fraction (MNF) transformation, (3) the calculation of the pixel purity index (PPI), (4) the n-dimensional visualization and extraction of endmember spectra, (5) the identification of endmember spectra for mineral occurrences and (6) the mapping of mineral occurrences. The identification of the extracted endmember spectra is obtained by comparing it with available pre-defined library spectra (United States Geological Survey (USGS), John Hopkins University (JHU) and Jet Propulsion Laboratory (JPL) spectral libraries) using the Spectral Analyst tool of ENVI 4.1 software (Research Systems Inc., Boulder, CO, US), which provides scores of matching. Three techniques, namely Spectral Feature Fitting (SFF), Spectral Angle Mapping (SAM) and Binary Encoding (BE), are used for identification of the collected endmember spectra to produce a score between 0 and 1, where the value of 1 equals a perfect match showing the exact mineral type. A total of six endmember spectra are identified and extracted in the study area. Mapping of mineral occurrences is carried out using the Mixture-Tuned Matched Filtering (MTMF) technique over the study area on the basis of collected and identified endmember spectra. Results of the present study using the ASA technique ascertain that Landsat ETM+ data can be used to generate valuable mineralogical information.

Delineation of structural features over a part of the Bay of Bengal using total and balanced horizontal derivative techniques

Abstract The present study deals with classical problem of edge detection in potential field data over complex tectonic regime for both shallower and deeper sources, simultaneously. Balanced horizontal derivative (BHD) technique is a latest edge detection concept which delineates edges using balancing of amplitude responses for both shallower and deeper sources. The BHD technique has been validated by comparing with total horizontal derivative (THD) technique. Initially, three different synthetic models have been generated with spherical, cylindrical and vertical prismatic objects at different depths and corresponding gravity responses have been enhanced using BHD and THD techniques. Structural features have been delineated from EIGEN6C4 free-air gravity data using THD and BHD techniques over a part of the Bay of Bengal. Major lineaments have been identified in N–S direction followed by those identified along the NE–SW, NW–SE and E–W directions. Both studies of synthetic models and real gravity data reveal that BHD is an advanced technique than THD.

Validation of ERS-1 and High-Resolution Satellite Gravity with in-situ Shipborne Gravity over the Indian Offshore Regions: Accuracies and Implications to Subsurface Modeling

Geoid and gravity anomalies derived from satellite altimetry are gradually gaining importance in marine geoscientific investigations. Keeping this in mind, we have validated ERS-1 (168 day repeat) altimeter data and very high-resolution free-air gravity data sets generated from Seasat, Geosat GM, ERS-1 and TOPEX/POSEIDON altimeters data with in-situ shipborne gravity data of both the Bay of Bengal and the Arabian Sea regions for the purpose of determining the consistencies and deviations. The RMS errors between high resolution satellite and ship gravity data vary from 2.7 to 6.0 mGal, while with ERS-1 data base the errors are as high as 16.5 mGal. We also have generated high resolution satellite gravity maps of different regions over the Indian offshore, which eventually have become much more accurate in extracting finer geological structures like 85° E Ridge, Swatch of no ground, Bombay High in comparison with ERS-1satellite-derived gravity maps. Results from the signal processing related studies over two specific profiles in the eastern and western offshore also clearly show the advantage of high resolution satellite gravity compared to the ERS-1 derived gravity with reference to ship gravity data.