Statistical landslide susceptibility assessment of the Mansehra and Torghar districts,Khyber Pakhtunkhwa Province,Pakistan

This paper presents laboratory experiments and numerical simulations of effects of submerged obstacles on tsunami-like solitary wave and its run-up. This study was carried out for the breaking and non-breaking solitary waves on 1:19.85 uniform slope which contains a submerged obstacle. New laboratory experiments are performed to describe the mitigation of tsunami amplitude and run-up under the effect of submerged obstacles. We are based on experimental results obtained to validate the numerical model. The numerical modeling using COULWAVE aims essentially to show the effect of the obstacle on the shape of solitary wave and the limit of this effect. Using a multiple nonlinear regression, we have determined a model to estimate height of run-up according to the amplitude of the wave and the obstacle peak depth.     

Exploitation of TerraSAR-X Data for Land use/Land Cover Analysis Using Object-Oriented Classification Approach in the African Sahel Area, Sudan

Recently, object-oriented classification techniques based on image segmentation approaches are being studied using high-resolution satellite images to extract various thematic information. In this study different types of land use/land cover (LULC) types were analysed by employing object-oriented classification approach to dual TerraSAR-X images (HH and HV polarisation) at African Sahel. For that purpose, multi-resolution segmentation (MRS) of the Definiens software was used for creating the image objects. Using the feature space optimisation (FSO) tool the attributes of the TerraSAR-X image were optimised in order to obtain the best separability among classes for the LULC mapping. The backscattering coefficients (BSC) for some classes were observed to be different for HH and HV polarisations. The best separation distance of the tested spectral, shape and textural features showed different variations among the discriminated LULC classes. An overall accuracy of 84 % with a kappa value 0.82 was resulted from the classification scheme, while accuracy differences among the classes were kept minimal. Finally, the results highlighted the importance of a combine use of TerraSAR-X data and object-oriented classification approaches as a useful source of information and technique for LULC analysis in the African Sahel drylands.     

High-resolution facies and porosity models of the upper Jurassic Arab-D carbonate reservoir using an outcrop analogue, central Saudi Arabia

Subsurface models of hydrocarbon reservoirs are coarse and of low resolution when compared with the actual geologic characteristics. Therefore, the understanding of the three-dimensional architecture of reservoir units is often incomplete. Outcrop analogues are commonly used to understand the spatial continuity of reservoir units. In this study, a Late Jurassic outcrop analogue for the Arab-D reservoir of central Saudi Arabia was used to build a high-resolution model that captures fine geologic details. Subsurface reservoir lithofacies were matched with those from the studied outcrop, and porosity values derived from published core and well log data from the Ain Dar, Uthmanyah, and Shudgum areas of the Ghawar Field, eastern Saudi Arabia, were then applied to the equivalent lithofacies in the outcrop. Maximum, minimum, and average subsurface porosity for each lithofacies were distributed in the facies model using a geostatistical algorithm to produce nine porosity models for the field data. Several realisations were run to visualise the variability in each model and to quantitatively measure the uncertainty associated with the models. The results indicated that potential reservoir zones were associated with grainstone, packstone, and some wackestone layers. Semivariogram analysis of the lithofacies showed good continuity in the N-S direction and less continuity in the E-W direction. The high-resolution lithofacies models detected permeability barriers and isolated low porosity bodies within the potential reservoir zones. This model revealed the porosity distribution in areas smaller than one cell in the subsurface model and highlighted the uncertainty associated with several aspects of the model.     

Paleoclimatic evolution of central Sudan during the Late Miocene to Pleistocene

In this paper, information derived from X-ray diffraction and heavy and light fractions analyses were discussed with the aim to trace the paleoclimatic changes of central Sudan during the Late Miocene to Pleistocene. Based on lithological and mineralogical characters noted in the Sayal and Umm Ruwaba Formations, four phases of distinct paleoclimatic changes were recognized. The first phase commenced in the Late Miocene during the deposition of the Sayal formation. The area was slightly uplifted and of gentle slope, a feature deduced from the deposition of clayey and fine-grained sandy materials with subordinate gravely component. A hot and humid climate, depicted from the development of kaolinite and iron oxide, is proposed during the deposition of the Sayal formation. The second phase is characterized by development of depressions in which alluvial streams and possibly small lacustrine basins occurred. This is inferred from the presence of sandy and silty materials, a characteristic of the lower and middle parts of the Umm Ruwaba Formation. The climate remained hot and humid during the deposition of the lower part of the Umm Ruwaba Formation in the early Pliocene. A shift to dry conditions with possible periodic humid seasons is, however, thought to be established during the deposition of the middle part of the Umm Ruwaba Formation deduced from the observed increase in salinity and decrease in iron oxide content. During the third phase, throughout the deposition of the upper part of the Umm Ruwaba Formation, the kinetic energy of streams increased as can be inferred from the presence of gravely intercalations. Deposition under arid climate is suggested for the lowermost part due to the increased amount of feldspars and the absence of iron oxide. However, evidence of cool condition is again noted at the topmost part of the formation inferred from the relatively high content of iron oxide in the deposits.     

Kernel Principal Component Analysis for Efficient,Differentiable Parameterization of Multipoint Geostatistics

This paper describes a novel approach for creating an efficient, general, and differentiable parameterization of large-scale non-Gaussian, non-stationary random fields (represented by multipoint geostatistics) that is capable of reproducing complex geological structures such as channels. Such parameterizations are appropriate for use with gradient-based algorithms applied to, for example, history-matching or uncertainty propagation. It is known that the standard Karhunen–Loeve (K–L) expansion, also called linear principal component analysis or PCA, can be used as a differentiable parameterization of input random fields defining the geological model. The standard K–L model is, however, limited in two respects. It requires an eigen-decomposition of the covariance matrix of the random field, which is prohibitively expensive for large models. In addition, it preserves only the two-point statistics of a random field, which is insufficient for reproducing complex structures. In this work, kernel PCA is applied to address the limitations associated with the standard K–L expansion. Although widely used in machine learning applications, it does not appear to have found any application for geological model parameterization. With kernel PCA, an eigen-decomposition of a small matrix called the kernel matrix is performed instead of the full covariance matrix. The method is much more efficient than the standard K–L procedure. Through use of higher order polynomial kernels, which implicitly define a high-dimensionality feature space, kernel PCA further enables the preservation of high-order statistics of the random field, instead of just two-point statistics as in the K–L method. The kernel PCA eigen-decomposition proceeds using a set of realizations created by geostatistical simulation (honoring two-point or multipoint statistics) rather than the analytical covariance function. We demonstrate that kernel PCA is capable of generating differentiable parameterizations that reproduce the essential features of complex geological structures represented by multipoint geostatistics. The kernel PCA representation is then applied to history match a water flooding problem. This example demonstrates that kernel PCA can be used with gradient-based history matching to provide models that match production history while maintaining multipoint geostatistics consistent with the underlying training image.     

Composition and sources of extractable organic matter from a sediment core in Lake Kivu,East African rift valley

Lake Kivu is a gas-charged East African rift lake with currently anoxic bottom water. The extractable compounds and residual organic matter of a short sediment core have δ¹³C values typical of lacustrine microbial detritus. The total extracts consist primarily of polar compounds such as n-alkanoic acids, hydroxyalkanoic acids, triterpenoids, steroids and monosaccharides, with minor amounts of n-alkanes and n-alkanols. These tracer compounds and δ¹³C values indicate that the organic matter in the surficial and deeper sedimentary record was dominated by bacterial sources. The sapropelic sediment between these horizons contains organic matter from primarily algal with lesser bacterial input. Terrestrial organic markers are minor in all samples. The major fractions of the compounds in the total extracts were oxidized in the upper water column prior to transit through the anoxic bottom water to sedimentary deposition. The sapropelic horizon may reflect lake water turnover with ventilation or hydrothermal activity and consequently increased algal blooms.     

Soil deformation and shear strength characteristics of the Sana''a soil, Yemen Arab Republic

Deformation and strength characteristics of the soil of Sana'a, the Yemen Arab Republic, were investigated. Undisturbed soil samples were collected fro used in consolidation, collapse and strength tests. The classical and critical state compressibility parameters were determined using a one-dimensional collapsing potential of the investigated soil was determined by using both qualitative and quantitative analysis. Consolidated undrained triaxial tests different types of samples: saturated samples and samples at natural moisture content. The stress history of the fine soils are in the range of normal except for the stiff fissured lean clay which exhibited a relatively high overconsolidated stress history. The loess formations exhibited a moderate to under wetting and loading. The investigated soils are characterized by having high shear strength when they have low moisture content and a drastic dec content increases.