2results about How to "Accurate quality" patented technology

The invention relates to the field of petroleum geological exploration reservoir evaluation, and discloses a compact sandstone reservoir quality evaluation method and related equipment, and the method comprises the following steps: determining reservoir indexes according to compact sandstone reservoir characteristics; determining a weight through an entropy weight method based on the reservoir indexes; constructing a target vector function by using an ideal point method based on the reservoir indexes; substituting the weights into a target vector function to obtain positive and negative ideal solutions; and constructing a reservoir quality model according to the positive and negative ideal solutions, and evaluating the reservoir quality of the tight sandstone reservoir based on the reservoir quality model. According to the method, the problem that the tight sandstone reservoir is difficult to evaluate is effectively solved, and a tight sandstone reservoir quality evaluation technology is formed.

This invention relates to the field of feed production, processing, and testing technology. Specifically, it relates to a feed production, processing, and testing method based on big data. The method includes the following steps: S1, collecting historical feed production data and screening it according to processing stages to obtain historical production data corresponding to each processing stage; S2, obtaining the feed quality corresponding to the historical production data, and simultaneously obtaining the standard process and standard quality corresponding to each processing stage. Through big data modeling, a deep correlation analysis between process and quality is achieved, significantly improving the accuracy of quality control. This not only quantifies the differences in feed quality and process deviations at each stage, but also innovatively introduces modeling of raw material quality grades and processing sequence nodes. By calculating the positive and negative values ​​of the impact of process deviations on quality, it accurately identifies the positive or negative destructive effects of fluctuations in different process parameters on quality.