Abstract: A method for assessing test adequacy of deep neural networks based on element decomposition is provided. The network testing is divided into black box testing and white box testing, of which key elements are decomposed and defined. Network parameters including a weight matrix and a bias vector are extracted. Importance values of neurons in individual layers of the deep neural network are calculated and clustered, and an importance value hot map of neurons in each layer is generated based on clustering results. Mutation testing, and index calculation and evaluation are performed.

Abstract: A well cementing method is described for improving cementing quality by controlling the hydration heat of cement slurry. By controlling the degree and/or rate of hydration heat release from cement slurry, the method improves the hydration heat release during formation of cement with curing of cement slurry, improves the binding quality between the cement and the interfaces, and in turn improves the cementing quality at the open hole section and/or the overlap section. The cementing method improves cementing quality of oil and gas wells and reduces the risk of annular pressure.