Geochemical characterization of the source rock intervals, Beni-Suef Basin, West Nile Valley, Egypt

Geochemical and lithological investigations in the WON C-3X well record five organic-matter-rich intervals (OMRIs) of effective source rocks. These OMRIs correspond to moderate and good potentials. Two of these intervals occurred within the L-Kharita member of the Albian age represent 60.97% of the entire Albian thickness. The rest of OMRIs belongs to the Abu-Roash G and F members of the Late Cenomanian–Santonian age comprising 17.52 and 78.66% of their total thickness, respectively. The calculated heat flow of the studied basin is high within the range of 90.1–95.55 mW/m2 from shallower Abu-Roash F to deeper L-Kharita members. This high-heat flow is efficient for shallowing in the maximum threshold expulsion depth in the studied well to 2,000 m and active source rock depth limit to 2,750 m. Thermal maturity and burial history show that the source rock of L-Kharita entered the oil generation from 97 Ma till the late oil stage of 7.5 Ma, whereas the younger Abu-Roash G and F members have entered oil generation since 56 Ma and not reached peak oil yet. Hence, the source rock intervals from Abu-Roash F and G are promising for adequate oil generation.

Determination of Spatial Variability of Rock Depth of Chennai

This study adopts four modeling techniques Ordinary Kriging(OK), Generalized Regression Neural Network (GRNN), Genetic Programming(GP) and Minimax Probability Machine Regression(MPMR) for prediction of rock depth(d) at Chennai(India). Latitude (Lx) and Longitude(Ly) have been used as inputs of the models. A semivariogram has been constructed for developing the OK model. The developed GP gives equation for prediction of d at any point in Chennai. A comparison of four modeling techniques has been carried out. The performance of MPMR is slightly better than the other models. The developed models give the spatial variability of rock depth at Chennai.

GIS APPROACH GEOSPATIAL APPLICATION FOR SEISMIC MICROZONATION STUDY

В работе представлен инструментарий в виде ГИС-технологий для составления карты сейсмического микрорайонирования. Рассмотрены методы и способы индийской и российской практики сейсмического микрорайонирования Реализована компиляция исходных данных в оперативную экспресс ГИС-методику. Построена карта сейсмического микрорайонирования первого уровня для города Ченнаи (Индия) с использованием ГИС-платформы на основе использования специфических информационных слоев в виде пикового ускорения грунта (PGA), скорости поперечной волны, геологического строения территории, уровня грунтовых вод и глубины кровли подстилающих коренных пород. Пиковое ускорение для сейсмических источников оценивалось на основе отношения затухания. При этом максимальное ускорение PGA для Ченнаи составило 0,176 g, а для Владикавказа – 0,2 g (для вероятности превышения 5%). Анализ сейсмической опасности включал матрицы данных (дискретные наборы данных из разных тем были преобразованы в сетки) для расчета окончательной матрицы сейсмической опасности путем интеграции и анализа веса исходных тематических слоев. Город Ченнай в процессе исследования был разделен на три обширные зоны: высокой, умеренной и низкой сейсмической опасности. Карта сейсмического микрорайонирования города Владикавказа была представлена в единицах шкалы MSK-64 и единицах ускорения. В обоих рассмотренных подходах скорости поперечных волн были одной из основных инструментальных основ для соответствующих расчетов. Используя в качестве исходных данных сценариев синтезированные расчетные записи с учетом характеристик неисправностей, учитывается трансформация исходных акселерограмм, обусловленных свойствами почвы на территории. In the paper GIS approach for seismic microzonation map compilation is presented. Approaches of Indian and Russian seismic microzonation practice are considered and compilated in express GIS technique. A first level seismic microzonation map of Chennai city has been produced with a GIS platform using the themes, viz, Peak Ground Acceleration (PGA), Shear wave velocity at 3 m, Geology, Ground water fluctuation and bed rock depth. The peak ground acceleration for these seismic sources were estimated based on the attenuation relationship and the maximum PGA for Chennai is 0.176 g and for Vladikavkaz 0.2 g (for 5% exceedance probability). The seismic microzonation analysis involved grid datasets (the discrete datasets from different themes were converted to grids) to compute the final seismic hazard grid through integration and weightage analysis of the source themes. The Chennai city has been classified into three broad zones, viz, High, Moderate and Low Seismic Hazard. Vladikavkaz city microzonation map was presented in MSK-64 scale. In both approaches shear wave velocities was one of the basic instrumental data. Using as initial data of the scenario synthesized records, taking into account the characteristics of faults, takes into account the transformation of the original accelerograms stipulated by soil properties of the territory.

Determination of Spatial Variability of Rock Depth of Chennai

This study adopts four modeling techniques Ordinary Kriging(OK), Generalized Regression Neural Network (GRNN), Genetic Programming(GP) and Minimax Probability Machine Regression(MPMR) for prediction of rock depth(d) at Chennai(India). Latitude (Lx) and Longitude(Ly) have been used as inputs of the models. A semivariogram has been constructed for developing the OK model. The developed GP gives equation for prediction of d at any point in Chennai. A comparison of four modeling techniques has been carried out. The performance of MPMR is slightly better than the other models. The developed models give the spatial variability of rock depth at Chennai.