建筑工程领域出现两种变革性的新技术:一种是新的建筑工程管理概念模式:精益建造(Lean Construction,LC);另一种则是新的信息技术:建筑信息模型(Building Information Modeling,BIM)。两者协同应用到工程实践中比单独应用其一所带来的...建筑工程领域出现两种变革性的新技术:一种是新的建筑工程管理概念模式:精益建造(Lean Construction,LC);另一种则是新的信息技术:建筑信息模型(Building Information Modeling,BIM)。两者协同应用到工程实践中比单独应用其一所带来的价值更大,所以探求两者间的交互关系很有意义。本文在详细分析精益建造原则和BIM技术功能的基础上,通过构建交互关系矩阵,探究两者间交互作用,并给出协同应用建议。本文研究可供工程项目参与各方制定精益建造和BIM技术应用策略时参考,指导工程实践,增加项目价值,提升行业效率。展开更多
Closed-loop production management combines the process of history matching and production optimization together to peri-odically updates the reservoir model and determine the optimal control strategy for production de...Closed-loop production management combines the process of history matching and production optimization together to peri-odically updates the reservoir model and determine the optimal control strategy for production development to realize the goal of decreasing the knowledge of model uncertainty as well as maximize the economic benefits for the expected reservoir life. The adjoint-gradient-based methods seem to be the most efficient algorithms for closed-loop management. Due to complicated calculation and limited availability of adjoint-gradient in commercial reservoir simulators, the application of this method is still prohibited for real fields. In this paper, a simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed for reservoir closed-loop production management with the combination of a parameterization way for history matching and a co-variance matrix to smooth well controls for production optimization. By using a set of unconditional realizations, the proposed parameterization method can transform the minimization of the objective function in history matching from a higher dimension to a lower dimension, which is quite useful for large scale history matching problem. Then the SPSA algorithm minimizes the objective function iteratively to get an optimal estimate reservoir model. Based on a prior covariance matrix for production op-timization, the SPSA algorithm generates a smooth stochastic search direction which is always uphill and has a certain time correlation for well controls. The example application shows that the SPSA algorithm for closed-loop production management can decrease the geological uncertainty and provide a reasonable estimate reservoir model without the calculation of the ad-joint-gradient. Meanwhile, the well controls optimized by the alternative SPSA algorithm are fairly smooth and significantly improve the effect of waterflooding with a higher NPV and a better sweep efficiency than the reactive control strategy.展开更多
文摘建筑工程领域出现两种变革性的新技术:一种是新的建筑工程管理概念模式:精益建造(Lean Construction,LC);另一种则是新的信息技术:建筑信息模型(Building Information Modeling,BIM)。两者协同应用到工程实践中比单独应用其一所带来的价值更大,所以探求两者间的交互关系很有意义。本文在详细分析精益建造原则和BIM技术功能的基础上,通过构建交互关系矩阵,探究两者间交互作用,并给出协同应用建议。本文研究可供工程项目参与各方制定精益建造和BIM技术应用策略时参考,指导工程实践,增加项目价值,提升行业效率。
基金supported by the National Natural Science Foundation of China (Grant No. 61004095F030202)the China Important National Sci-ence & Technology Specific Projects (Grant No. 2008ZX05030-05-002)+1 种基金the Fundamental Research Funds for the Central Universities (Grant No. 09CX05007A)the National Basic Research Program of China (Grant No. 2011CB201000)
文摘Closed-loop production management combines the process of history matching and production optimization together to peri-odically updates the reservoir model and determine the optimal control strategy for production development to realize the goal of decreasing the knowledge of model uncertainty as well as maximize the economic benefits for the expected reservoir life. The adjoint-gradient-based methods seem to be the most efficient algorithms for closed-loop management. Due to complicated calculation and limited availability of adjoint-gradient in commercial reservoir simulators, the application of this method is still prohibited for real fields. In this paper, a simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed for reservoir closed-loop production management with the combination of a parameterization way for history matching and a co-variance matrix to smooth well controls for production optimization. By using a set of unconditional realizations, the proposed parameterization method can transform the minimization of the objective function in history matching from a higher dimension to a lower dimension, which is quite useful for large scale history matching problem. Then the SPSA algorithm minimizes the objective function iteratively to get an optimal estimate reservoir model. Based on a prior covariance matrix for production op-timization, the SPSA algorithm generates a smooth stochastic search direction which is always uphill and has a certain time correlation for well controls. The example application shows that the SPSA algorithm for closed-loop production management can decrease the geological uncertainty and provide a reasonable estimate reservoir model without the calculation of the ad-joint-gradient. Meanwhile, the well controls optimized by the alternative SPSA algorithm are fairly smooth and significantly improve the effect of waterflooding with a higher NPV and a better sweep efficiency than the reactive control strategy.
