In this paper we apply the streamline-based production data integration method to condition a multimillion cell geologic model to historical production response for a giant Saudi Arabian reservoir. The field has been under peripheral water injection with 16 injectors and 70 producers. There is also a strong aquifer influx into the field. A total of 30 years of production history with detailed rate, infill well and reperforation schedule were incorporated via multiple pressure updates during streamline simulation. Also, gravity and compressibility effects were included to account for water slumping and aquifer support. To our knowledge, this is the first and the largest such application of production data integration to geologic models accounting for realistic field conditions. We have developed novel techniques to analytically compute the sensitivities of the production response in the presence of gravity and changing field conditions. This makes our method extremely computationally efficient. For the field application, the production data integration is carried out in less than 6 hours in a PC.The geologic model derived after conditioning to production response was validated using field surveillance data. In particular, the flood front movement, the aquifer encroachment and bypassed oil locations obtained from the geologic model was found to be consistent with field observations. Finally, an examination of the permeability changes during production data integration revealed that most of these changes were aligned along the facies distribution, particularly the 'good' facies distribution with no resulting loss in geologic realism. TX 75083-3836, U.S.A., fax 01-972-952-9435.

This approach has been derived mainly to improve quality and efficiency of global path planning for a mobile robot with unknown static obstacle avoidance features in grid-based environment. The quality of the global path in terms of smoothness, path consistency and safety can affect the autonomous behavior of a robot. In this paper, the efficiency of Ant Colony Optimization (ACO) algorithm has improved with additional assistance of A * Multi-Directional algorithm. In the first part, A * Multi-directional algorithm starts to search in map and stores the best nodes area between start and destination with optimal heuristic value and that area of nodes has been chosen for path search by ACO to avoid blind search at initial iterations. The path obtained in grid-based environment consist of points in Cartesian coordinates connected through line segments with sharp bends. Therefore, Markov Decision Process (MDP) trajectory evaluation model is introduced with a novel reward policy to filter and reduce the sharpness in global path generated in grid environment. With arc-length parameterization, a curvilinear smooth route has been generated among filtered waypoints and produces consistency and smoothness in the global path. To achieve a comfort drive and safety for robot, lateral and longitudinal control has been utilized to form a set of optimal trajectories along the reference route, as well as, minimizing total cost. The total cost includes curvature, lateral and longitudinal coordinates constraints. Additionally, for collision detection, at every step the set of optimal local trajectories have been checked for any unexpected obstacle. The results have been verified through simulations in MATLAB compared with previous global path planning algorithms to differentiate the efficiency and quality of derived approach in different constraint environments.

BackgroundIschemic stroke is one of the main causes of death and disability worldwide. It is caused by the cessation of cerebral blood flow resulting in the insufficient delivery of glucose and oxygen to the neural tissue. The inflammatory response initiated by ischemic stroke in order to restore tissue homeostasis in the acute phase of stroke contributes to delayed brain damage.MethodsBy using in vitro models of neuroinflammation and in vivo model of permanent middle cerebral artery occlusion, we demonstrate the neuroprotective and anti-inflammatory effects of sulfosuccinimidyl oleate sodium (SSO).ResultsSSO significantly reduced the lipopolysaccharide/interferon-γ-induced production of nitric oxide, interleukin-6 and tumor necrosis factor-α, and the protein levels of inflammatory enzymes including nitric oxide synthase 2, cyclooxygenase-2 (COX-2), and p38 mitogen-activated protein kinase (MAPK) in microglia, without causing cell toxicity. Although SSO failed to directly alleviate glutamate-induced excitotoxicity in murine cortical neurons, it prevented inflammation-induced neuronal death in microglia-neuron co-cultures. Importantly, oral administration of SSO in Balb/c mice subjected to permanent occlusion of the middle cerebral artery reduced microglial activation in the peri-ischemic area and attenuated brain damage. This in vivo neuroprotective effect of SSO was associated with a reduction in the COX-2 and heme oxygenase-1 immunoreactivities.ConclusionsOur results suggest that SSO is an anti-inflammatory and a possible therapeutic candidate in diseases such as stroke where inflammation is a central hallmark.

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