matlab求解微分方程组代码-reservoir_datasets:各种油藏数据集，包括Volve和PUNQS3
matlab优化微分方程组代码自述文件
这些数据集的目的是将它们用于在Pyhon中使用机器学习库及其派生概念验证（POC）进行测试。
由于PyTorch具有与图形处理单元或GPU一起使用的内置功能，因此我们期望在开始全面移植MRST之前进行演示，基于PyTorch
GPU的张量可以显着减少储层模拟期间的计算时间。
评价概念验证
步骤如下：
找到构成MRST求解器代码的偏微分方程（PDE）。
使用Matlab和Octave测试求解器的运行时间。
最新的《使用MATLAB进行储层模拟入门》一书（Knut-Andreas
Lie的Octave
）中提供了一些测试代码。
见附录。
正在Matlab和Octave下测试代码的性能。
代码将发布在单独的存储库中。
使用PyTorch
for
GPU复制Python中的功能。
将Matlab代码转换为PyTorch
测量原始MRST求解器的计算时间。
如果在PyTorch计算时间快10到100，我们将继续将更多的Matlab代码转换为基于PyTorch张量的计算。
数据集
MRST（下载）
固相萃取9
固相萃取10
案例B4
赛格
OPM
固相萃取1
文件下载
资源详情
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