1·The structural deformation is the principal geological factor that affects the thickness variation of coal seam on a mine field scale.
构造作用是控制井田范围内煤层厚度变化的主要地质因素。
2·The field scale spatial variability of soil properties is one of the key factors which have considerable effect on water flow and solute transport.
田块尺度土壤特性的空间变异性对水分与溶质运移具有明显的影响。
3·Due to great spatial variability of this hydraulic property, direct measurement seems to be infeasible and even impossible, especially for a field scale problem.
对于一个较大范围的实际问题，由于其在空间和时间上的强烈变异性，采用直接实验大量测定通常是不可行的。
4·The basin evolution, hydrocarbon generation, resource abundant, oil and gas field scale are different between two basins since they are located on different tectonic setting.
由于两盆地所处的区域构造背景不同，致使其盆地演化、成烃演化、资源丰度、油气田规模差异很大。
5·Through analysis of the field scale samples in Wuqi oilfield by X-ray diffraction method, scaling causes and scale control measures are studied in downhole and gathering system.
采用X -射线衍射方法分析了吴旗油田现场垢样成分，进而研究了吴旗油田井下及集输系统结垢原因和防垢措施。
6·Dynamic crop growth simulation models have been developed at a plot or a field scale. However, crop growth monitoring and yield predication at regional scale are concerned by decision makers.
作物生长模型是在田间尺度上开发的，而区域尺度上的作物生长信息更受决策部门的关注。
7·The unique design is based on extensive battlefield experience in full scale and low intensity conflicts, and attests to Elbit systems' leadership in the field of turret and fire control systems.
系统的独特设计是基于各种规模、低强度冲突中积累的广泛的战场经验，并证明了埃尔比特系统在炮塔和火控系统领域的领先地位。
8·Virtual Field activities are best used in prototype applications or in smaller scale applications where the amount of data and the size of the application's NSF file is not of concern.
Virtual Field 活动最好使用在原型应用程序中或更小规模的应用程序中，在这样的应用程序中，数据的数量和应用程序 NSF 文件的大小无关紧要。
9·Imagine if we were shooting on a football field, and we have a room, which is maybe 10 meters by 5; we can scale that room up to fit the football field.
想像一下，我们要拍摄一个在足球场上的片段，而我们只有一个10*5的房间，但我们可以通过调整房间大小来满足足球场的尺寸。
10·It is of a larger scale compared to other datasets in the field (over 300m ratings).
它相对于这个领域中其他数据集要大得多(超过300m评分)。