The distribution of fractures is highly uncertain in naturally fractured reservoirs (NFRs) and may be predicted by using the assisted-history-matching (AHM) that calibrates the reservoir model according to some high-quality static data combined with dynamic production data. A general AHM approach for NFRs is to construct a discrete fracture network (DFN) model and estimate model parameters given the observations. However, the large number of fractures prediction required in the AHM process could pose a high-dimensional optimization problem. This difficulty is particularly challenging when the fractures form a complex multi-scale fracture network. We present in this paper an integrated AHM approach of NFRs to tackle these challenges. Two essential ingredients of the method are (1) a 2D fractal-DFN model constructed as the geological simulation model to describe the complex fracture network, and (2) a mixture of multi-scale parameters, built according to the fractal-DNF model, as an inversion parameter model to alleviate the high-dimensional optimization burden caused by complex fracture networks. A reservoir with a multi-scale fracture network is set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the fractures well recognized by assimilating production data.
The objective of this paper is to analyze the air distribution and comfort in large space environment simulator under different air supply for the same boundary and initial conditions. This is done by conducting the numerical simulations and contrasting the distribution of velocity and temperature field, PMV-PPD and air age. It can be analyzed that the influence of several air supply on air quality and thermal comfort inside the equipment, which can be as a reference for the improvement and optimization of airflow distribution with the device. This device owns three openable doors, which locate in the bottom, middle and top of the equipment. Open one of them, the ventilation will be achieved. Computational Fluid Dynamics (CFD) is used for it is easier and less time consuming to accomplish that purpose. In general, different air supply have important effect on the air distribution and comfort inside the device. Meanwhile, the comfort is acceptable in most area, however, the air age is on the high side.
Target controllability is an interesting property of complex network and attracts many researchers from different fields. However, controlling large natural or technological networks is a great challenge. But it is not feasible and sometimes unnecessary to control the entire network, hence target control seems efficient in this situation. The greedy algorithm was developed and offers a good approximation to calculate the minimum number of driver nodes, where control signals are injected, for control the target nodes in the network. Based on the target control theory, we investigate the target controllability of directed Erdős-Rényi and the Barabási-Albert networks under attack or failure. Results show that degree-based node attack is more efficient than random attacks in directed BA networks on network target controllability but the similar in directed ER networks.
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