Parallel history matching and associated forecast at the center for interactive smart oilfield technologies

We have developed a parallel and distributed computing framework to solve an inverse problem, which involves massive data sets and is of great importance to petroleum industry. A Monte Carlo method, combined with proxies to avoid excessive data processing, is employed to identify reservoir simulation models that best match the oilfield production history. Subsequently, the selected models are used to forecast future productions with uncertainty estimates. The parallelization framework combines: (1) message passing for tightly coupled intra-simulation decomposition; and (2) scheduler/Grid remote procedure calls for model parameter sweeps. A preliminary numerical test has included 3,159 simulations on a 256-processor Intel Xeon cluster at the USC-CACS. The results provide uncertainty estimates of unprecedented precision.     

Simple assay method for endocrine disrupters by in vitro quail embryo culture: nonylphenol acts as a weak estrogen in quail embryos

Many chemicals that are not structurally related to estrogen have estrogen-like activity. In this study, we tried to apply a quail embryo culture system for assessing the in vivo effects of such chemicals on the development of quail embryos. Beta-estradiol induced feminization of the gonads of genetically male embryos, which was confirmed by the increase in the size of the left gonad and female-specific aromatase expression, while male-specific SOX9 expression was not affected. Nonylphenol, which has a weak estrogenic activity, reduced the viability and body weight of embryos. Simultaneously, several genetically male embryos were feminized in terms of gonadal size and aromatase expression. These results indicate that the avian embryo culture system was useful for evaluating endocrine disrupters.