The Prediction of the Performance of an Oil Reservoir by Proxy Model

Simulation model of an undeveloped oil reservoir is full of uncertainty. Assessing the effect of these parameters on the simulation results, is very important task in reservoir engineering. Making a proxy model is a method for forecast reservoir performance under different production scenarios. In this study, GMDH-type neural network is used as a proxy model and also Experimental Design theory is used to get the most information full data set which is applied to the input of the neural network. The traditional way needs to very large number of simulation but this method is very time consuming and costly. A sensitivity analysis was conducted to understand the most important initial parameters. In this study, proxy model is created to predict FOPR, Field Oil Production Rate, in a reservoir under immiscible gas injection scenario to 15 years.

1913-1914: the First Truly International Year of Crystallography

It is appropriate that 2014 has been chosen as the International Year of Crystallography since it was a century ago that crystallography as we know it emerged as a truly international science. The pattern becomes clearer if one considers academic years starting on September 1. Thus 1911-1912, when the first successful diffraction experiments were carried out, becomes the German year of crystallography. With the statement of Bragg's Law and the first structure determinations, 1912-1913 can be called the British year of crystallography. By late 1913 our science had achieved truly international scope, demonstrated by publications describing advances in experimental design, theory and structure determination emanating from France, Japan, the Netherlands, Russia and Switzerland as well as Germany and Britain. While many countries worked on the first two areas, structure determination was done mainly in Britain (dominated by the Braggs) and Japan (to a limited extent). In the belligerent countries this magnificent flowering was sadly curtailed by the outbreak of World War I. However, at about this time the United States entered the field. The international spread followed by curtailment is readily visualised when presented in the form of a timeline.

Optimal design of experiments on nematode dynamics and crop yield

Experimental design theory provides tools to estimate parameters of nematode dynamics and yield loss functions with the highest accuracy given the available budget for the experiment. Variables in models, which take the role of predictors, are given values and a weight so that the best result is obtained. As a side result the prediction of the response will have a minimal variance. We introduce the concept of D-optimum design and consider in our models two response variables: the nematode density at the end of the season and the crop yield. Both variables depend on the same predictor, the initial nematode density. D-optimum design applies to linear regression models. For models that are nonlinear in the parameters, as is the case in this study, a linearisation at a given point in a parameter plane is used. When the initial nematode density at the experimental units is known prior to experimentation, one may optimally allocate the treatments to the units by selecting the combination that has the highest efficiency.