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FORECASTING HYDROCARBON RESERVOIR PROPERTIES WITH ARTIFICIAL INTELLIGENCE

机译:预测人工智能的烃储层特性

摘要

Systems, methods, and apparatus including computer-readable mediums for forecasting hydrocarbon reservoir properties such as well log responses and petrophysical parameters using artificial intelligence are provided. In one aspect, a method of forecasting well logs of a target well includes obtaining well data of the target well including depth and geological information and reservoir parameters and estimating jointly multiple well logs of the target well by utilizing an artificial intelligence (AI) network with the well data of the target well. The AI network is trained based on well data of existing wells that includes multiple reservoir parameters of the existing wells jointly as inputs and multiple well logs of the existing wells jointly as outputs. The estimated multiple well logs of the target well are reconciled with each other, with the well logs of the existing wells, and with geographic formation associated with the target well and the existing wells.
机译:提供了用于预测烃储层性质的计算机可读介质的系统,方法和装置,例如使用人工智能的井对数响应和岩石物理参数。 在一个方面,预测目标井的井日志的方法包括获得目标良好的井数据,包括深度和地质信息和储库参数,并通过利用人工智能(AI)网络来估计目标井的联合多孔日志 目标井的井数据。 AI网络基于现有井的井数据培训,该数据包括现有井的多个储库参数,作为现有井的输入和与输出共同的多孔记录。 估计目标井的估计的多孔日志与现有井的井日志和与目标井相关联的地理形成和现有的井。

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