Stochastic modeling techniques have been widely applied to oil-gas reservoir lithofacies.Markov chain simulation~however~is still under development~mainly because of the difficulties in reasonably defining conditional...Stochastic modeling techniques have been widely applied to oil-gas reservoir lithofacies.Markov chain simulation~however~is still under development~mainly because of the difficulties in reasonably defining conditional probabilities for multi-dimensional Markov chains and determining transition probabilities for horizontal strike and dip directions.The aim of this work is to solve these problems.Firstly~the calculation formulae of conditional probabilities for multi-dimensional Markov chain models are proposed under the full independence and conditional independence assumptions.It is noted that multi-dimensional Markov models based on the conditional independence assumption are reasonable because these models avoid the small-class underestimation problem.Then~the methods for determining transition probabilities are given.The vertical transition probabilities are obtained by computing the transition frequencies from drilling data~while the horizontal transition probabilities are estimated by using well data and the elongation ratios according to Walther's law.Finally~these models are used to simulate the reservoir lithofacies distribution of Tahe oilfield in China.The results show that the conditional independence method performs better than the full independence counterpart in maintaining the true percentage composition and reproducing lithofacies spatial features.展开更多
Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and thei...Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and their employees have hired the enterprise cloud services, and put much important information in the cloud gradually. Cloud service systems have become the main targets of malicious attacks. However, the cloud computing technologies are still not perfect, and the management and maintenance of enterprise cloud services are more complex compared to traditional network services of cloud computing. So, enterprise cloud services are more likely to encounter some security problems, and the influenced scale of these security problems is broad. But there are few researches on the security of enterprise cloud services. In this paper, we analyze the software as a service（Saa S） enterprise cloud services and introduce the research status of security problems in cloud computing environment. Combining with the analysis of the characteristics and application architecture of Saa S enterprise cloud services, we propose the security problems analysis model, the analysis system architecture and the relational model. Our researches can support further research of the automatic generation of solutions and guide the deployment of security policies of Saa S enterprise cloud services.展开更多
基金Project(2016YFB0503601)supported by the National Key Research and Development Program of ChinaProject(41730105)supported by the National Natural Science Foundation of China
文摘Stochastic modeling techniques have been widely applied to oil-gas reservoir lithofacies.Markov chain simulation~however~is still under development~mainly because of the difficulties in reasonably defining conditional probabilities for multi-dimensional Markov chains and determining transition probabilities for horizontal strike and dip directions.The aim of this work is to solve these problems.Firstly~the calculation formulae of conditional probabilities for multi-dimensional Markov chain models are proposed under the full independence and conditional independence assumptions.It is noted that multi-dimensional Markov models based on the conditional independence assumption are reasonable because these models avoid the small-class underestimation problem.Then~the methods for determining transition probabilities are given.The vertical transition probabilities are obtained by computing the transition frequencies from drilling data~while the horizontal transition probabilities are estimated by using well data and the elongation ratios according to Walther's law.Finally~these models are used to simulate the reservoir lithofacies distribution of Tahe oilfield in China.The results show that the conditional independence method performs better than the full independence counterpart in maintaining the true percentage composition and reproducing lithofacies spatial features.
基金supported by National Natural Science Foundation of China(Nos.61300049,61502197 and 61503044)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20120061120059)+2 种基金the China Postdoctoral Science Foundation(No.2011M500612)the Key Program for Science and Technology Development of Jilin Province of China(No.20130206052GX)the Natural Science Research Foundation of Jilin Province of China(Nos.20140520069JH,20150101054JC and 20150520058JH)
文摘Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and their employees have hired the enterprise cloud services, and put much important information in the cloud gradually. Cloud service systems have become the main targets of malicious attacks. However, the cloud computing technologies are still not perfect, and the management and maintenance of enterprise cloud services are more complex compared to traditional network services of cloud computing. So, enterprise cloud services are more likely to encounter some security problems, and the influenced scale of these security problems is broad. But there are few researches on the security of enterprise cloud services. In this paper, we analyze the software as a service（Saa S） enterprise cloud services and introduce the research status of security problems in cloud computing environment. Combining with the analysis of the characteristics and application architecture of Saa S enterprise cloud services, we propose the security problems analysis model, the analysis system architecture and the relational model. Our researches can support further research of the automatic generation of solutions and guide the deployment of security policies of Saa S enterprise cloud services.
