Abstract
Recently, the number of studies devoted to the use of machine learning methods in geophysics has been increasing. Examples of such studies include the prediction of rock properties and separation of rock types according to quantitative characteristics. Annotated datasets are required to build machine learning based models. The purpose of this paper is to review open labeled well datasets and some research used these datasets. Datasets from competitions in machine learning for geophysical problems are analyzed, as well as other publicly available sources of open well data. The paper considers datasets containing well logging, rock images, laboratory research results, as well as labeled zonation by lithotypes.
Publisher
Keldysh Institute of Applied Mathematics