Contents of January 2005 - Vol. XXVI No.1

PRESIDENTIAL ADDRESS "LEVERAGING KNOWLEDGE BASE IN HYDROCARBON EXPLORATION IN INDIA - KEY DRIVER FOR BRIDGING DEMAND - SUPPLY GAP
- Y.B.Sinha

NEURAL NETWORKS AND THEIR APPLICATIONS IN LITHOSTRATIGRAPHIC INTERPRETATION OF SEISMIC DATA FOR RESERVOIR CHARACTERISATION
- M.Chandra, A.K.Srivastava, V.Singh, D.N.Tiwari and P.K.Painuly

PRELIMINARY FIRST LEVEL SEISMIC MICROZONATION OF GUWAHATI
- M.Baranwal, B.Pathak and S.M.Syiem

GEOLOGY AND TECTONICS OF NORTH EAST INDIA
- S.K.Acharyya

SEISMOTECTONICS OF INDIA WITH SPECIAL REFERENCE TO NORTH EAST REGION
- J.R.Kayal


PRESIDENTIAL ADDRESS "LEVERAGING KNOWLEDGE BASE IN HYDROCARBON EXPLORATION IN INDIA - KEY DRIVER FOR BRIDGING DEMAND-SUPPLY GAP"

Y.B.Sinha

Director (Exploration), Oil &Natural Gas Corporation and President, AEG

Abstract

Exploration & Production sector, traditionally, is a knowledge-based industry. In the current context in India, as we target new objectives in established sectors and venture into logistically difficult & geologically ancient areas on one hand and the cost intensive deep water domains on the other, leveraging the emerging knowledge base assumes importance and becomes focus for a collective approach. This conference, with its focal theme of “Petroleum Exploration in India-Emerging knowledge base” will therefore provide the most appropriate platform, at the present juncture, as the Country is taking a giant step forward, in its endeavor to expand the E&P horizon to the new frontiers, envisioning enhancement in domestic supply. In this seminar, with valuable participation of experts from different domains of Geoscience, we will be able to map the emerging knowledge base in various fields in order to leverage them to find more oil and gas in the domestic acreages in the years to come. May I place before you, a few essential components of the available knowledge base in hydrocarbon exploration.

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NEURAL NETWORKS AND THEIR APPLICATIONS IN LITHOSTRATIGRAPHIC INTERPRETATION OF SEISMIC DATA FOR RESERVOIR CHARACTERISATION

M.Chandra, A.K.Srivastava, V.Singh, D.N.Tiwari and P.K.Painuly

Geodata Processing and Interpretation Centre, Oil and Natural Gas Corporation Limited, Dehradun

Abstract

Paradigm shift in hydrocarbon exploration and development strategies has increased utilization of seismic data many fold for reservoir characterization. To establish the complicated and nonlinear relationship between seismic attributes and reservoir properties has been a major challenge for working geoscientists in synergistic interpretation. This problem has recently been addressed through artificial neural network techniques. The artificial neural networks are able to couple the speed and efficiency of the computer with pattern recognition, prediction and association capability of the brain to aid the petroleum exploration process. In this paper, an attempt has been made to give a brief introduction of neural networks and their way of working. The neural network classifications based on training methods in unsupervised and supervised category have been described. Unsupervised neural networks analysis presumes no prior knowledge of the object to be classified and neural network looks for pattern itself during seismic facies classification. In supervised analysis, reservoir properties are predicted away from the boreholes in inter-well regions after establishing the relation between multi-seismic attributes and well log data. The effectiveness of these neural network techniques in interpretation has been demonstrated through a real data example. In study area, a series of thin clastic reservoirs are sandwiched between coal and shale layers and are discrete in nature. These multi-pay sands having thickness from 2m to 8m are the main hydrocarbon producers. Severe lateral lithological variation has affected the porosity distribution in these reservoirs. Low porosity zones are found devoid of hydrocarbons. A systematic interpretation approach was adopted to delineate these multi-pay thin reservoirs in the study area. This includes well log analysis and their correlation, well to synthetic calibration, horizon tracking, structural mapping and reservoir characterization. For better reservoir characterization, Kohonen self organized maps (K-SOM) for seismic facies classification, synthetic modeling, seismic amplitude attribute and post stack seismic inversion analysis to delineate the reservoir sand, and probabilistic neural networks (PNN) to predict effective porosity distribution of reservoir sand are used. The seismic facies, amplitude attribute, spectral decomposition and acoustic impedance maps were helpful in providing more meaningful geological information about the extent, shape and lateral lithology variation of reservoir sands. The effective porosity maps generated using artificial probabilistic neural networks (PNN) have provided effective porosity distribution with an acceptable degree of confidence. This systematic approach of interpretation along with neural network techniques has helped in understanding the subsurface image and internal reservoir properties. This has added a significant value to the exploration and development of hydrocarbons in the study area.

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PRELIMINARY FIRST LEVEL SEISMIC MICROZONATION OF GUWAHATI

M.Baranwal, B.Pathak and S.M.Syiem

Geophysics Division, Geological Survey of India, North Eastern Region, Shillong

Abstract

First level microzonation map of Guwahati has been prepared based on amplification of ground motion, slope of exposed rocks, shape and constituents of overburden material inferred from geophysical surveys. The map reflects local ground conditions. For map preparation liquefaction and amplification of ground motion has been emphasised, as they are most important earthquake hazards. Microzonation maps generally are prepared at 3 levels. Level-I map is basic amplification susceptibility map. It shows soil units grouped on the basis of their relative susceptibility to amplification, geologic and geotechnical data and uses a relative susceptibility descriptor based on soil categories. The map shows susceptibility of the ground to amplification of seismic motions relative to firm ground or rock motions at the same location. The soil profiles have been categorised in terms of their susceptibility to amplification. Where bedrock is very deep, the soil susceptibility categories of the uppermost 35 m of soil profile that generally has the greatest influence on amplification has been considered. The soil susceptibility categories defined according to soil type, thickness and stiffness has been taken as the basis for defining mapping units. Considering these factors map has been prepared which depicts the thickness of soils above bedrock based on geophysical results. The resistivity surveys carried out in the area have been analysed. The seismic studies carried out show that Vs ranges from 166 to 330 m/s and corresponding amplification ratios varies from 3.1 to 2.2. The damage ratio (DR) calculated from these values were found to be 0.2 and 0.05. The Rayleigh wave propagating through hard ground is magnified as it enters a two-layered ground with a soft surface layer. In the portions near to rock exposures this type of configuration prevails, hence magnification may be predominant. Rayleigh wave propagation relative to basin configuration has been taken to account for preparation of the map.

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GEOLOGY AND TECTONICS OF NORTHEAST INDIA

S.K.Acharyya

Department of Geological Sciences, Jadavpur University, Kolkata

Abstract

The NE Himalaya and the Indo-Burma mountain belts are linked and veer round the prolongation of the Shillong-Mikir continental promontory to form the “Eastern Himalayan Syntaxis”. Marine to paralic facies early Palaeogene sediments interbanded with the Abor Volcanics are exposed beneath the arched up MBT at the core of the Siang Window developed close to the syntaxis. These sediments are also exposed intermittently in thrust slivers in the MBT zone along the frontal belt. A few domal windows have developed north of the frontal belt. These and the Siang windows may have been formed in a similar way. It is postulated that thickened sections of the Plaeogene sediments may be present in sub-surface at the cores of some windows. The Himalayan foreland basin had sporadic Eocene Continental Flood Basalt activity, which may be caused by deep faults that developed soon after India-Asia continental collision. The setting of the Assam shelf southeast of the Shillong-Mikir massif, is very similar to that of East-Coast of India and an oceanic margin possibly occurs close to this shelf. The Indo-Burma Range, to its east, possibly has a continental or transitional crust foundation, which is named “Indo-Burma-Andaman” (IBA) block. The northern end of the IBA collided with the NE leading edge of the Indian continent during the Pliocene. Similar assemblage of ophiolites that were mainly accreted during the mid Eocene occurs along two parallel belts: one along the Indo-Burma Range and other along the Central Burma volcanic line. The latter represent the Late Oligocene collision suture between the IBA and the Central Burma (CB) blocks, wherefrom the ophiolites were thrust westward on the IBR as flat-lying nappes. The Indian continent was separated from the amalgamated IBA-CB block by the Indian Ocean, which was narrower to the north but open to the south. The presently active subduction along the Java-Andaman trench was initiated along the western margin of the amalgamated IBA-CBB block, since late Miocene and it caused N-Q volcanism and opened the Andaman Sea. The ophiolites exposed as flatlying nappies in the IBR are unrelated to the currently active subduction or to the eastern limit of the Indian plate. Thick Neogene sequence of the relatively deeper water Surma sediments and the overlying Tipam sediments in the Mizoram-Tripura fold belt appear to have formed over the subducting Indian Ocean crust. In the Naga-Assam foothills further north, the Neogene sequence comprising the Surma, Tipam and Namsang are fluvial in nature. These sediments are imbricated during the Pliocene in the “belt of schuppen” due to the convergence and collision of the IBA block and the Indian continent. The suture between the Indian and the IBA appears to be concealed beneath the Disang thrust.

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SEISMOTECTONICS OF INDIA WITH SPECIAL REFERENCE TO NORTH EAST REGION

J.R. Kayal

Geological Survey of India, 27, J.L. Nehru Road, Kolkata

Abstract

The geophysical data in the Indian ocean floor suggest that India got separated from the Antarctica and Australia during Cretaceous. The Indian plate travelled north and northeastward in between the Ninety East Ridge and Chagos-Laccedive transfrom fault during Cenozoic (e.g. Curray et al.,1982). The Indian continent had to travel 1000 km before achieving its initial contact with the Eurasian plate in late Cretaceous to early Eocene. This contact in the north is demarcated as the Himalayan arc, and in the east as the Burmese arc. Many authors have suggested that the Himalayan arc is now involved in a continent-continent collision, whereas the Burmese arc is involved in a subduction process. The Burmese arc is linked with the Andaman – Sunda arc to the south where subduction process of the Indian plate is continued. Intense seismic activity is observed in Himalayan arc as well as in the Burmese – Andaman – Sunda arc. The Himalaya, the Indo-Burma ranges and the adjoining northeast India region is marked as a high seismic zone, zone V, in the seismic zoning map of India. Four great earthquakes (M>8.0) occurred in this zone; from east to west these are : the 1950 Assam earthquake (M 8.7) and the 1897 Shillong earthquake (M 8.7) in the northeast region, the 1934 Bihar earthquake (M 8.4) in the foothills of central Himalaya and the 1905 Kangra earthquake (M 8.6) in the western Himalaya. While the Himalaya is a region of dominant compressional tectonics,the peninsular India is a region marked by early Archaean cratonisation with associated Proterozoic belts. The Indo Gangetic Alluvial Plains, a region of less eventful recent sedimentation, separates the peninsular India from the Himalaya. Except the western margin, which produced the 1918 great Kutch earthquake (M 8.4) and falls in the zone V, the Indian peninsular is known as a stable cratonic subcontinent. The intraplate seismicity is low, but in the recent past three devastating earthquakes occurred in the peninsular India region. Seismotectonics of the Himalaya, Indo-Burma ranges and peninsular India earthquakes are briefly discussed with a special reference to the northeast India region

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