Machine learning approach to inter-well radio wave survey data imaging

Abstract

Inter-well measurements are used to reduce drilling costs with no reduce small kimberlite body detection. The radio wave method enables measurement of the apparent absorption coefficient that is proportional to the effective electrical resistance of the rock. Our point is to build a three-dimensional model of distribution of electrical properties of inter-well space throughout the entire exploration region. The measured data is distributed unevenly because data points are grouped along the linear clusters. The distance between neighbor points composing a cluster is much smaller than distance between clusters. In terms of geostatistics, this means a significant spatial anisotropy of data distribution that is difficult to take into account using standard geostatistical approach. We have shown that the problem could be solved by methods developed within the theory of machine learning. To build a three-dimensional model of attenuation coefficient we used a modified method of -nearest neighbors.KEYWORDS: inter-well scanning; radio wave survey; machine learning; kNN-algorithm.Citation: Aleshin, I. M. and I. V. Malygin (2019), Machine learning approach to inter-well radio wave survey data imaging, Russ.

Geomagnetic Survey Interpolation with the Machine Learning Approach

“…As previously mentioned in the Introduction, the distribution of the resulting data set b i (x i , y i ) is strongly inhomogeneous and anisotropic. Similarly to the case of earlier research [Aleshin and Malygin, 2019], we will use the approach described there. To do this, we will switch to a coordinate system where the the ordinate axis is parallel to the long lines of the flight path (Figure 4).…”

“…Be it noted that the equivalent situation occurs during the crossborehole electromagnetic imaging. In our paper [Aleshin and Malygin, 2019] it was shown that the problem can be solved with a scale transformation of one of the axis. Similarly, we used the method for processing geomagnetic survey results in this paper.…”