根据电磁探测和实验室测量,岩石热物理特性构造

В. В. Спичак, А.Г. Гойдина, О.К. Захарова
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引用次数: 0

摘要

进行了热导率、比热容和表面热流密度的可行性研究。研究表明,根据电磁声数据和岩石样品的实验室测量,神经网络预测的热物理性质不仅可以在井眼以下,而且可以在井间空间估计这些性质,相对精度约为6-10%,具体取决于训练数据量和预测数据量之间的比例。沿大地电磁测深剖面建立了研究区地表“干”、“暖”导热系数剖面、比热容剖面和热流密度剖面。
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ПОСТРОЕНИЕ РАЗРЕЗОВ ТЕПЛОФИЗИЧЕСКИХ СВОЙСТВ ПОРОД ПО ДАННЫМ ЭЛЕКТРОМАГНИТНЫХ ЗОНДИРОВАНИЙ И ЛАБОРАТОРНЫХ ИЗМЕРЕНИЙ
Feasibility studies aimed at building of the thermal conductivity and specific heat capacity as well as heat flow density at the surface are carried out. It is shown that neural network forecast of the thermo-physical properties from electromagnetic sound data and laboratory measurements on the rock samples enables estimating these properties not only below the boreholes but also in the interwell space with relative accuracy around 6-10% depending on the ratio between the volumes of training and forecasted data. Sections of “dry” and “warm” thermal conductivity, specific heat capacity and a profile of the heat flow density at the surface of the study area are built along mgnetotelluric sounding profile.
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