Narrow Density Window and Risk Assessment Based on Big Data

Abstract

For the deep strata with fracture zone, fault zone and various permeability and fracture loss, the geological conditions are particularly complicated, which makes it particularly difficult to predict the safety density window and engineering risk, through investigation and research, combined with the actual situation of a deep oil and gas reservoirs in northwest China, for the formation of three pressure section in the regions was determined, and through the actual leakage occurs correction of formation fracture pressure of drilling fluid density as a standard of lost circulation project risk evaluation, the author combined with big data, based on a certain algorithm, got the regionalization of the region narrow safe density window, on narrow density window combination of generalized stress and strength interference theory, based on the real-time drilling fluid density in the region one of the key Wells project risk evaluation, the project risk is match with the actual project risk situation

DBSCAN Clustering Algorithm Based on Big Data Is Applied in Network Information Security Detection

“…Using the birch algorithm for clustering can effectively extract clusters of arbitrary shape and correctly identify noise points and outliers, but the space-time complexity is higher than using DBSCAN. Both methods require users to provide several threshold parameters, which increases the difficulty of clustering algorithm in practical application [5,6]. erefore, combined with the birch algorithm and DBSCAN algorithm, an improved clustering algorithm is proposed, which enables the algorithm to use a heuristic adaptive algorithm to estimate some threshold parameters of the clustering algorithm, avoids the setting of threshold parameters directly by users, and reduces the difficulty of clustering algorithm in practical application.…”

The Application of Big Data and Artificial Intelligence Technology in Enterprise Information Security Management and Risk Assessment

“…In terms of malware detection, some researchers proposed the use of ML and feature extraction methods for classification, such as the use of SVMs and random forests for classification of malicious code (Bar, 2022;Diebig et al, 2022). In terms of RA, some methods using ML and DM techniques for RA were proposed, such as using naïve Bayes algorithm for network attack detection and clustering algorithm for vulnerability scanning (Li et al, 2021;Krans et al, 2022).…”

Application of Entropy Hierarchy Analysis and Deep Neural Network Algorithm Combination in Enterprise Economic Management

“…With the rapid development of the economy and the deepening of the research on enterprise business performance, it was gradually found that the influence of nonfinancial elements on enterprise business performance should not be underestimated. e early 20th century extended the evaluation of enterprise business performance to nonfinancial fields and carried out comprehensive evaluation of enterprise business performance [4]. Accordingly, the Ministry of Finance issued a series of policy specifications, such as the Operating Rules for Enterprise Business Performance Evaluation, the Interim Measures for Performance Evaluation of Financial State-Owned and State-Controlled Enterprises, and the Interim Measures for Management of Business Performance Evaluation of Central Enterprises [5].…”