Patent classifications
G01N2021/5919
Reticle transmittance measurement method, projection exposure method using the same, and projection exposure device
When a reticle is first used, the reticle is loaded in a projection exposure device and measured by either oblique measurement or random measurement, thereby avoiding the fear of uneven sampling and determining the reticle transmittance of the entire reticle as the parent population, without increasing the sampling count. The same effect can be obtained by making the measurement spot size, which is fixed in general, variable and by changing the angle of incidence in relation to the measurement spot size.
RETICLE TRANSMITTANCE MEASUREMENT METHOD, PROJECTION EXPOSURE METHOD USING THE SAME, AND PROJECTION EXPOSURE DEVICE
When a reticle is first used, the reticle is loaded in a projection exposure device and measured by either oblique measurement or random measurement, thereby avoiding the fear of uneven sampling and determining the reticle transmittance of the entire reticle as the parent population, without increasing the sampling count. The same effect can be obtained by making the measurement spot size, which is fixed in general, variable and by changing the angle of incidence in relation to the measurement spot size.
Determining reservoir fluid properties from downhole fluid analysis data using machine learning
Methods for determining in situ the value of a formation fluid parameter using a downhole fluid analysis (DFA) tool. The methods utilize advanced statistical learning tools to build a predictive model to estimate a fluid property given a set of input parameters. In one embodiment the fluid saturation pressure parameter is determined by using the DFA tool to obtain the fluid and to obtain weight fractions of at least C.sub.1, C.sub.6+, and CO.sub.2 of the fluid. The weight fractions and a reservoir temperature are input into a trained statistical learning machine to obtain a determination of the saturation pressure of the fluid.