CMWRXVI – Delineation of Geologic Facies with Support Vector Machines
نویسندگان
چکیده
The ability to delineate geologic facies and to estimate their properties from sparse data is essential for modeling physical and biochemical processes occurring in the subsurface. If such data are poorly differentiated, this challenging task is complicated further by preventing a clear distinction between different hydrofacies even at locations where data are available. We study the problem of facies delineation in geologic formations by means of the Support Vector Machine (SVM). To show the potential of the SVM, we randomly generate a twodimensional porous medium composed of two heterogeneous materials, and then reconstruct boundaries between these materials from a few data points. We assess the performance and accuracy of the SVM-based facies delineation technique and assess in the presence of either well differentiated or poorly differentiated information about hydraulic parameters, such as hydraulic conductivity.
منابع مشابه
Delineation of geologic facies with statistical learning theory
[1] Insufficient site parameterization remains a major stumbling block for efficient and reliable prediction of flow and transport in a subsurface environment. The lack of sufficient parameter data is usually dealt with by treating relevant parameters as random fields, which enables one to employ various geostatistical and stochastic tools. The major conceptual difficulty with these techniques ...
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