Computing derivative information of sequentially coupled subsurface models

A generic framework for the computation of derivative information required for gradient-based optimization using sequentially coupled subsurface simulation models is presented. The proposed approach allows for the computation of any derivative information with no modification of the mathematical framework. It only requires the forward model Jacobians and the objective function to be appropriately defined. The flexibility of the framework is demonstrated by its application in different reservoir management studies. The performance of the gradient computation strategy is demonstrated in a synthetic water-flooding model, where the forward model is constructed based on a sequentially coupled flow-transport system. The methodology is illustrated for a synthetic model, with different types of applications of data assimilation and life-cycle optimization. Results are compared with the classical fully coupled (FIM) forward simulation. Based on the presented numerical examples, it is demonstrated how, without any modifications of the basic framework, the solution of gradient-based optimization models can be obtained for any given set of coupled equations. The sequential derivative computation methods deliver similar results compared to FIM methods, while being computationally more efficient.     

Gravimetric and magnetic fabric study of the Sintra Igneous complex: laccolith-plug emplacement in the Western Iberian passive margin

International Journal of Earth Sciences - The geometry and emplacement of the ~ 96 km2, Late Cretaceous Sintra Igneous complex (SIC, ca. 80 Ma) into the West Iberian passive...     

The Juchatengo complex: an upper-level ophiolite assemblage of late Paleozoic age in Oaxaca,southern Mexico

International Journal of Earth Sciences - The Juchatengo complex (JC) suite is located between the Proterozoic Oaxacan complex to the north and the Xolapa complex to the south, and was amalgamated...     

Impact of irrigated agriculture on groundwater-recharge salinity: a major sustainability concern in semi-arid regions

Intensive irrigated agriculture substantially modifies the hydrological cycle and often has major environmental impacts. The article focuses upon a specific concern—the tendency for progressive long-term increases in the salinity of groundwater recharge derived from irrigated permeable soils and replenishment of unconfined aquifers in more arid regions. This process has received only scant attention in the water-resource literature and has not been considered by agricultural science. This work makes an original contribution by analysing, from scientific principles, how the salinisation of groundwater recharge arises and identifies the factors affecting its severity. If not proactively managed, the process eventually will impact irrigation waterwell salinity, the productivity of agriculture itself, and can even lead to land abandonment. The types of management measure required for mitigation are discussed through three detailed case histories of areas with high-value groundwater-irrigated agriculture (in Spain, Argentina and Pakistan), which provide a long-term perspective on the evolution of the problem over various decades.     

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias,NW Spain)

Given its geological and climatic conditions and its rugged orography, Asturias is one of the most landslide prone areas in the North of Spain. Most of the landslides occur during intense rainfall episodes. Thus, precipitation is considered the main triggering factor in the study area, reaching average annual values of 960 mm. Two main precipitation patterns are frequent: (i) long-lasting periods of moderate rainfall during autumn and winter and (ii) heavy short rainfall episodes during spring and early summer. In the present work, soil moisture conditions in the locations of 84 landslides are analysed during two rainfall episodes, which represent the most common precipitation patterns: October–November 2008 and June 2010. Empirical data allowed the definition of available water capacity percentages of 99–100% as critical soil moisture conditions for the landslide triggering. Intensity-duration rainfall thresholds were calculated for each episode, considering the periods with sustained high soil moisture levels before the occurrence of each analysed landslide event. For this purpose, data from daily water balance models and weather stations were used. An inverse relationship between the duration of the precipitation and its intensity, consistent with published intensity-duration thresholds, was observed, showing relevant seasonal differences.