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Twelve normal, active faults transverse to the regional Ganga and Yamuna longitudinal faults have been identified in the western part of the gently sloping Upper Gangetic Plain from the interpretation of digital elevation models (DEMs), prepared by manual digitization of spot heights from 1 : 50 000 scale topographic maps. High vertical exaggeration of these DEMs reveals artefactual morphostructures such as 'cliffs' and 'significant breaks in slopes' that are indicative of faults. Convergent drainage on the upthrown blocks, initiation of new streams on the downthrown blocks, offsetting of drainage and anomalous sinuosity of streams close to faults have provided additional corroborating evidence of the faults. Detailed field investigations indicate relatively steeper slopes close to the inferred faults than the adjoining areas. Erosion of the upthrown blocks and deposition of sediments on the downthrown blocks in the form of terminal fans under a semi-arid climate formed features typical of many such faults.

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The effects of sample holding times, sample storage, and sample preservation in the laboratory have considerable effects on the final results of standard SRA (source rock analysis). This research was primarily directed to determine the potential effects of delay in processing and analysis. For example, over time; will the volatile hydrocarbon content (S1) and hydrocarbon generative potential (S2) [which is used to calculate Hydrogen Index (HI) and Production Index (PI)] show consistent results? In total fifteen samples were analysed for source rock analysis using the industry standard SRA-TPH/TOC instrument to test the effect of wait time on SRA results. Results from experiments conducted for variations in the sample holding time in shale rock samples show statistically meaningful changes. The samples that were processed and analyzed within one to three days show significant S1 and S2 values whereas the same samples analysed after four weeks and subsequently after three months show declining trends. The change between the four week and three month analysis is almost negligible. The noted average change in S1, S2 and S3 values ranges between 2% to 14%, 1% to 9% and 0% to 12%, respectively. Since the HI and PI are calculated from the S1 and S2 values, they also show lower values, averaging 5.26% and 3.75%, respectively. The same samples were also analyzed for clay contents and brittleness. The samples with high clay content and lower brittleness index show greater decline in the S1 and S2 values, and conversely, low clay content at higher brittleness show less decline in the S1 and S2 values. Therefore, more lithified/cemented samples show less variability over long holding times. In addition, the experimental results obtained indicate that sample holding time also demonstrate there are considerable effects on the final results when the S1 and S2 values are especially high. In order to avoid the sample degradation and data consistency issues, there is an industry-wide need to reassess sample collection, storage, processing, and analysis time. Although the data set analyzed may not be sufficient to make broad conclusions concerning the changes in the data, as there are several other confounding factors to take into account. However, the approaches demonstrated in this study will assist future researchers with more comprehensive data sets.

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