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51.
Natural Resources Research - In surface mines and underground excavations, every blasting operation can have some destructive environmental impacts, among which air overpressure (AOp) is of major...  相似文献   
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Magnetotelluric (MT) and ground magnetic surveys were conducted on the Mahallat geothermal field situated in Markazi province, central Iran, as a primary part of the explorations and developments of a geothermal energy investigation program in the region. Mahallat region has the greatest geothermal fields in Iran. MT survey was performed in November 2011 on an 8 km profile crossing the hot springs with a total of 17 stations. The 2D inversion of the determinant MT data was performed using a 2D inversion routine based on the Occam approach. The 2D resistivity model obtained from the determinant data shows a low resistivity zone at 800-2000 m depth and a higher resistivity zone above the low resistivity zone, interpreted as geothermal reservoir and cap rock, respectively. It also revealed two major concealed faults which are acting as preferential paths for the circulation of hydrothermal fluids. To obtain more geophysical evidence, a ground magnetic survey with 5000 stations was also performed over an area of 200 km2 around the MT profile. Magnetic measurements show a main positive anomaly of about +1000 nT over the study area, which could be interpreted as an intrusive body with the high magnetic susceptibility (i.e. mafic and ultramafic rocks) into the sedimentary host rocks. We interpret the body as the heat source of the geothermal system. Structural index and depth estimation of the anomaly indicate that the intrusive body is similar to a cylinder extending from about one kilometer depth down to greater depths. The results of MT and magnetic investigations indicate a geothermal reservoir which proves the preliminary geological observations to a great extent.  相似文献   
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Mathematical Geosciences - Characterization of field-scale reservoir connectivity is critical for production optimization and field development planning. The information content of the data...  相似文献   
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Current land administration systems mainly use 2D plans to define and secure ownership rights associated with properties in high‐rise buildings. These 2D plans may not effectively communicate and manage the spatial complexity associated with multi‐layered and stacked properties in such buildings; additionally, multiple pages of plans (representing sections of the building) are required to represent all ownership boundaries. In response, land administration organizations have been investigating a 3D digital approach to managing information about ownership rights in high‐rise building structures. In this article, Building Information Modeling (BIM) is proposed as a feasible approach for managing land and property information in high‐rise buildings. BIM provides a collaborative, digital and intelligent 3D data environment for managing building information throughout the lifecycle of buildings. However, there is currently no capacity in BIM for recording and representing information about ownership and boundaries of properties, which is core land administration information. Therefore, this article proposes an extension to the BIM standard, which is implemented in a prototype BIM model of a complex building to showcase the potential capability of using BIM for high‐rise land administration and for modeling 3D ownership rights.  相似文献   
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Development of subsurface energy and environmental resources can be improved by tuning important decision variables such as well locations and operating rates to optimize a desired performance metric. Optimal well locations in a discretized reservoir model are typically identified by solving an integer programming problem while identification of optimal well settings (controls) is formulated as a continuous optimization problem. In general, however, the decision variables in field development optimization can include many design parameters such as the number, type, location, short-term and long-term operational settings (controls), and drilling schedule of the wells. In addition to the large number of decision variables, field optimization problems are further complicated by the existing technical and physical constraints as well as the uncertainty in describing heterogeneous properties of geologic formations. In this paper, we consider simultaneous optimization of well locations and dynamic rate allocations under geologic uncertainty using a variant of the simultaneous perturbation and stochastic approximation (SPSA). In addition, by taking advantage of the robustness of SPSA against errors in calculating the cost function, we develop an efficient field development optimization under geologic uncertainty, where an ensemble of models are used to describe important flow and transport reservoir properties (e.g., permeability and porosity). We use several numerical experiments, including a channel layer of the SPE10 model and the three-dimensional PUNQ-S3 reservoir, to illustrate the performance improvement that can be achieved by solving a combined well placement and control optimization using the SPSA algorithm under known and uncertain reservoir model assumptions.  相似文献   
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Some facility for the prevention of piping, reducing exit gradient and seepage amount under hydraulic structures, is construction of cutoff wall and drain. Therefore, this study compares the efficiency of cutoff wall on some design parameters in an assumed diversion dam cross-section. For this purpose, different placements of cutoff wall with various angle of inclination were used in the dam foundation. Results of this study showed that minimum uplift pressure happens when cut off wall is in the heel (upstream) of the dam. With fixing of longitudinal cut off wall placement, inclination of cutoff wall respect to the vertical position, results in reducing of uplift pressure. Effect of inclination of cutoff wall in upstream of the dam; respect to vertical position, in reducing of uplift pressure is very high.  相似文献   
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Multiple-point statistics (MPS) provides a flexible grid-based approach for simulating complex geologic patterns that contain high-order statistical information represented by a conceptual prior geologic model known as a training image (TI). While MPS is quite powerful for describing complex geologic facies connectivity, conditioning the simulation results on flow measurements that have a nonlinear and complex relation with the facies distribution is quite challenging. Here, an adaptive flow-conditioning method is proposed that uses a flow-data feedback mechanism to simulate facies models from a prior TI. The adaptive conditioning is implemented as a stochastic optimization algorithm that involves an initial exploration stage to find the promising regions of the search space, followed by a more focused search of the identified regions in the second stage. To guide the search strategy, a facies probability map that summarizes the common features of the accepted models in previous iterations is constructed to provide conditioning information about facies occurrence in each grid block. The constructed facies probability map is then incorporated as soft data into the single normal equation simulation (snesim) algorithm to generate a new candidate solution for the next iteration. As the optimization iterations progress, the initial facies probability map is gradually updated using the most recently accepted iterate. This conditioning process can be interpreted as a stochastic optimization algorithm with memory where the new models are proposed based on the history of the successful past iterations. The application of this adaptive conditioning approach is extended to the case where multiple training images are proposed as alternative geologic scenarios. The advantages and limitations of the proposed adaptive conditioning scheme are discussed and numerical experiments from fluvial channel formations are used to compare its performance with non-adaptive conditioning techniques.  相似文献   
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