MODEL-BASED TRANSFORMATIONS OF COMMON MIDPOINT GATHERS1

A method for transforming Normal Moveout corrected CMP-gathers is proposed. The method is based upon the availability of a model of the CMP-gather. However, the transformation can be performed with any degree of accuracy in the model. Ideally the employed model should be a synthesis of all available a priori information about the particular data set. Mathematically the transformation is performed as follows. The CMP-gather is considered to be a matrix. This matrix is first decomposed into a set of submatrices of the same dimensions. Each submatrix consists of non-zero elements or samples with the same relative amount of noise. By reducing each of these submatrices to a vector (a trace) we get a new set of traces. This set then represents the transformed CMP-gather. The purpose of the transformation is to organize the CMP data in a form which makes it easier both to analyse the noise distribution and to take the necessary steps to improve the signal-to-noise ratio at the stacking stage. In principle the method incorporates the exploitation of multichannel recordings with the use of models. Several examples of transformed gathers and their applications to the improvement of real seismic data are shown.     

Modelling for forest growing stock assessment using satellite data — A case study

The satellite digital vegetation index data has been correlated with the forest growing stock by fitting linear regression models. The goodness of fit was tested. The analysis showed that the vegetation index which is the ratio of reflectance of vegetation in near infrared band to red wave band of electromagnetic spectrum is highly correlated to forest growing stock and the same can be used to predict the volume in remote forest areas for quick assessment purpose. Implications for future forest inventory are discussed.     

SUPERSTACK—AN ITERATIVE STACKING ALGORITHM*

An algorithm for separation of signals according to their coherency is proposed. The algorithm, called Superstack, is used on common depth point data after normal moveout corrections have been applied. The algorithm can be regarded as an iterative stacking procedure. After each stack, input values are changed depending on the consistency of the output of the previous stack. The Superstack algorithm is able to provide better separation of signals showing a different degree of horizontal consistency (coherency) than the normal horizontal stack. All noise signals in a CDP-gather may be assumed to show less horizontal consistency than the primary reflections. On this basis the algorithm will give an improved primary/multiple and an improved primary/noise ratio. The Superstack is very general, should not be especially expensive in terms of computer time, and can easily be implemented in routine processing.     

Application of directional filtering in lineament mapping for groundwater prospecting around bhinmal — A semi arid part of thar desert

The significance of neotectonic lineaments for groundwater prospecting was studied for the area around Bhinmal — a semi-arid part of Thar desert. The application of Directional Filtering procedures on IRS LISS I Band 4 digital image of the study area revealed NE-SW, NW-SE and E-W trending lineaments which are very subtle and in two cases, even unnoticed otherwise. The use of exploratory borehole lithologs and field evidences indicated that the identified lineaments are long rectilinear buried and partly exposed channels and the intersection zones are characterised by thick lenses of coarse sand and gravel. These buried channels and zones of coarse sediments thus represent potential sites for the accumulation of freshwater during rain. The present work has highlighted the suitability of Directional Filtering procedures for lineament mapping and buried channel studies in a desertic terrain.     

Cloud condensation nuclei spectra derived from size distributions and hygroscopic properties of the aerosol in coastal south-west Portugal during ACE-2

In this work we propose and test a method to calculate cloud condensation nuclei (CCN) spectra based on aerosol number size distributions and hygroscopic growth factors. Sensitivity studies show that this method can be used in a wide variety of conditions except when the aerosol consist mainly of organic compounds. One crucial step in the calculations, estimating soluble ions in an aerosol particle based on hygroscopic growth factors, is tested in an internal hygroscopic consistency study. The results show that during the second Aerosol Characterization Experiment (ACE-2) the number concentration of inorganic ions analyzed in impactor samples could be reproduced from measured growth factors within the measurement uncertainties at the measurement site in Sagres, Portugal.
CCN spectra were calculated based on data from the ACE-2 field experiment at the Sagres site. The calculations overestimate measured CCN spectra on average by approximately 30%, which is comparable to the uncertainties in measurements and calculations at supersaturations below 0.5%. The calculated CCN spectra were averaged over time periods when Sagres received clean air masses and air masses influenced by aged and recent pollution. Pollution outbreaks enhance the CCN concentrations at supersaturations near 0.2% by a factor of 3 (aged pollution) to 5 (recent pollution) compared to the clean marine background concentrations. In polluted air masses, the shape of the CCN spectra changes. The clean spectra can be approximated by a power function, whereas the polluted spectra are better approximated by an error function.     

Land transformation in Punjab — A case study of Kapurthala district

The map showing the extent of salt affected and sand dune soils was prepared at 1:50,000 scale using Landsat TM data for March 1987 and compared with the soil map of Kapurthala district based on 1965 aerial photographs and semi detailed survey of the district during 1975–76. The study revealed that in a span of 22 years (1965 to 1986) the area of sand dunes decreased from 22.7 per cent to 2.3 per cent and that of salt affected soils from 20.95 per cent to 4.38 per cent respectively as a consequence of reclamation of salt affected soils and clearing and levelling of sand dunes. Salt affected soils after reclamation have been brought under paddy-wheat rotation. Whereas sand dunes after clearing and levelling, have been brought under wheat or wheat -rice/fodder/oilseed crops.     

IMPROVEMENT OF MULTICHANNEL SEISMIC DATA THROUGH APPLICATION OF THE MEDIAN CONCEPT1

Different types of median-based methods can be used to improve multichannel seismic data, particularly at the stacking stage in processing. Different applications of the median concept are described and discussed. The most direct application is the Simple Median Stack (SMS), i.e. to use as output the median value of the input amplitudes at each reflection time. By the Alpha-Trimmed Mean (ATM) method it is possible to exclude an optional amount of the input amplitudes that differ most from the median value. A more novel use of the median concept is the Weighted Median Stack (WMS). This method is based on a long-gapped median filter. The implicit weighting, which is purely statistical in nature, is due to the edge effects that occur when the gapped filter is applied. By shifting the traces around before filtering, the maximum weight may be given to, for example, the far-offset traces. The fourth method is the Iterative Median Stack (IMS). This method, which also includes a strong element of weighting, consists of a repeated use of a gapped median filter combined with a gradual shortening of the filter after each pass. Examples show how the seismic data can benefit from the application of these methods.