【摘要】 在油气开发领域,经常采用网格模型对地形进行描述,当采样数据点分布相对规则时,可以快速建立网格模型,而当采样数据点不规则分布时,建立网格模型则比较困难。为此,提出了一种基于GPU并行加速的快速建模方法:首先分离规则分布数据和不规则分布数据;然后根据数据特征建立适合不规则数据的规则网格模型,并利用GPU加速修正网格,从而实现了不规则数据的规则化;最后进行三角形剖分并通过OpenGL绘制。试验结果表明,该方法能够处理不规则分布的大数据并在保持较高逼真度的前提下大幅度提升了建模速度,适用于复杂地质体的快速建模。更多还原

【Abstract】 In the field of oil and gas exploration,the terrain is often described by mesh model.When the distribution of sampling data is relatively regular,a mesb model can be built rapidly.While it is irregularly distributed,it is more difficult to be modeled.A method of fast modeling based on parallel GPU acceleration is presented on this paper.In the method,the regularly distributed data are separated from the irregular distributed ones firstly,and then the regularmesh models that fit the irregular data are built according to its feature,during the process,the powerful parallel computing capability of GPU is used to correct mesh vertices for the regulation of irregular data.Eventually,the mesh models are processed with triangle subdivision technique and drawn by OpenGL.With the above method,it can improve the speed for modeling the irregular data for maintaining high fidelity.The experimental results show that the method can be applied to process irregular distributed big data and greatly increase the speed of modeling:it is very applicable to the rapid modeling of complex geological mass as well.更多还原