Optimized double kriging algorithm for the geological environment parameters modeling

The geological environment parameters are widely used in the hydrocarbon deposits exploration and study. They store information about the rocks physical characteristics, the location of the reservoirs, the boundaries of the layers separation, etc. The numerical values of the parameters under consideration are obtained by conducting geophysical well logging (GWL), or by recalculating existing logging curves based on known petrophysical laws. Because GWL can be carried out only if there is a drilled well, the environment parameters are often known only in a small near-wellbore space. This makes urgent the task of predicting the geological environment parameters within the entire field. The existing methods for solving this task can be conditionally divided into two groups: using only GWL data; complexly using 3D seismic and GWL data. The first group is effective when there is a dense grid of downhole measurements. The second group shows the best results in the conditions of a sparse irregular grid, however, it requires the seismic data availability within the entire studied field. This paper describes a new method for predicting geological environment parameters based on the GWL data and 3D seismic prospecting combined use. The paper also provides an algorithmic implementation of the new method; ways of optimizing algorithmic implementation are considered.

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