On a damaging earthquake-induced landslide in the Algerian Alps: the March 20, 2006 Laâlam landslide (Babors chain,northeast Algeria), triggered by the Kherrata earthquake (<Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript> = 5.3)

On March 20, 2006, an earthquake (M _w = 5.3; SED) struck the mountainous region of the Babors chain (Wilaya of Bejaia, northeast Algeria). The seismic epicenter was located near the Kherrata village. This earthquake was felt on a large area of the northeastern part of Algeria. It reached an intensity of VII (EMS scale) at the Laalam village, situated at about 20 km northeast of Kherrata. Here, many old and recent houses were damaged or collapsed totally, four people died and 68 were injured. Field investigations revealed that these casualties were caused by a landslide triggered by the earthquake. Many fissures were visible on ground throughout the site. They were generated by both sliding and settling phenomena. The Laalam site is prone to landslide, as revealed by some evidences on old instabilities. This is due to two main factors: local geomorphology and geology. These factors intervene synchronously for reducing the slope instability at the Laalam village. The March 20, 2006 Kherrata earthquake was the trigger that released the Laalam landslide.     

Estimating the Depth of Stratigraphic Units from Marine Seismic Profiles Using Nonstationary Geostatistics

The object of this study is to build a three-dimensional (3D) geometric model of the stratigraphicunits of the margin of the Rhone River on the basis of geophysical investigations by a networkof seismic profiles at sea. The geometry of these units is described by depth charts of eachsurface identified by seismic profiling, which is done by geostatistics. The modeling starts bya statistical analysis by which we determine the parameters that enable us to calculate thevariograms of the identified surfaces. After having determined the statistical parameters, wecalculate the variograms of the variable Depth. By analyzing the behavior of the variogramwe then can deduce whether the situation is stationary and if the variable has an anisotropicbehavior. We tried the following two nonstationary methods to obtain our estimates: (a) Themethod of universal kriging if the underlying variogram was directly accessible. (b) Themethod of increments if the underlying variogram was not directly accessible. After havingmodeled the variograms of the increments and of the variable itself, we calculated the surfacesby kriging the variable Depth on a small-mesh estimation grid. The two methods then arecompared and their respective advantages and disadvantages are discussed, as well as theirfields of application. These methods are capable of being used widely in earthsciences forautomatic mapping of geometric surfaces or for variables such as a piezometricsurface or aconcentration, which are not stationary, that is, essentially, possess a gradient or a tendencyto develop systematically in space.     

Variogram Identification Aided by a Structural Framework for Improved Geometric Modeling of Faulted Reservoirs: Jeffara Basin, Southeastern Tunisia

This article describes a proposed work-sequence to generate accurate reservoir-architecture models, describing the geometry of bounding surfaces (i.e., fault locations and extents), of a structurally complex geologic setting in the Jeffara Basin (South East Tunisia) by means of geostatistical modeling. This uses the variogram as the main tool to measure the spatial variability of the studied geologic medium before making any estimation or simulation. However, it is not always easy to fit complex experimental variograms to theoretical models. Thus, our primary purpose was to establish a relationship between the geology and the components of the variograms to fit a mathematically consistent and geologically interpretable variogram model for improved predictions of surface geometries. We used a three-step approach based on available well data and seismic information. First, we determined the structural framework: a seismo-tectonic data analysis was carried out, and we showed that the study area is cut mainly by NW–SE-trending normal faults, which were classified according to geometric criteria (strike, throw magnitude, dip, and dip direction). We showed that these normal faults are at the origin of a large-scale trend structure (surfaces tilted toward the north-east). At a smaller scale, the normal faults create a distinct compartmentalization of the reservoirs. Then, a model of the reservoir system architecture was built by geostatistical methods. An efficient methodology was developed, to estimate the bounding faulted surfaces of the reservoir units. Emphasis was placed on (i) elaborating a methodology for variogram interpretation and modeling, whereby the importance of each variogram component is assessed in terms of probably geologic factor controlling the behavior of each structure; (ii) integrating the relevant fault characteristics, which were deduced from the previous fault classification analysis, as constraints in the kriging estimation of bounding surfaces to best reflect the geologic structure of the study area. Finally, the estimated bounding surfaces together with seismic data and variogram interpretations were used to obtain further insights into the tectonic evolution of the study area that has induced the current reservoirs configuration.     

Seismic hazard assessment in the megacity of Blida (Algeria) and its surrounding regions using parametric-historic procedure

The region of Blida is characterized by a relatively high seismic activity, pointed especially during the past two centuries. Indeed, it experienced a significant number of destructive earthquakes such as the earthquakes of March 2, 1825 and January 2, 1867, with intensity of X and IX, respectively. This study aims to investigate potential seismic hazard in Blida city and its surrounding regions. For this purpose, a typical seismic catalog was compiled using historical macroseismic events that occurred over a period of a few hundred years, and the recent instrumental seismicity dating back to 1900. The parametric-historic procedure introduced by Kijko and Graham (1998, 1999) was applied to assess seismic hazard in the study region. It is adapted to deal with incomplete catalogs and does not use any subjective delineation of active seismic zones. Because of the lack of recorded strong motion data, three ground prediction models have been considered, as they seem the most adapted to the seismicity of the study region. Results are presented as peak ground acceleration (PGA) seismic hazard maps, showing expected peak accelerations with 10% probability of exceedance in 50-year period. As the most significant result, hot spot regions with high PGA values are mapped. For example, a PGA of 0.44 g has been found in a small geographical area centered on Blida city.     

Prediction of sediment yield at storm period in Northwest Algeria

This paper studies the hydrodynamics and variability of stream flow and sediment yield in Wadi El Hammam, located in the semi-arid region of Algeria. In this location, hysteresis effects are obvious especially during high discharge periods. The sediment concentration and load maxima go several months before discharge maxima, while decreased sediment concentrations are noticed during the discharge peaks. In order to explain these phenomena, we have adopted a methodology that consists of finding a simple regression model capable of explaining the sediment load as a function of the water discharge measured at gauging stations of three rivers at various scales, e.g., annual and seasonal. Suspended sediment concentrations are measured during a 22-year period (1986/1987–2007/2008). The results have shown that the power model explains the greatest part of the variance (80%). The changes in sediment availability result in so-called hysteresis effects. In this work, we have described different loops: clockwise or positive hysteresis loops and anti- or counter-clockwise hysteresis loops. The analysis of the seasonal sediment yields has shown that the autumn season contributes a large proportion of the annual sediment yield (62%).