Implementation of Geostatistical Algorithms

Abstract

The state of nature is uncertain. Andre G. Journel championed the concept that we must quantify our uncertainty, then make a risk-qualified decision. The theory for this concept applied to the earth sciences was developed by Andre and others over the past four decades. Theory is unquestionably important, but the implementation of theory in algorithms and practical workflows has always been an essential aspect of geostatistics. This motivated the geostatistical software library and other computer codes. The effort remains unfinished. The workflows for the quantification of geological uncertainty and risk-qualified decision making are achievable to a select few who are comfortable bending arcane software to their will. The routine calculation of probabilistic resources and risk qualified decision making requires a clarity of vision or, as Andre was fond of saying, an understanding of the essence. The essential steps required for constructing numerical models that effectively quantify our state of nature have emerged. The concepts for risk-qualified decision making are clear. Practitioners have technical solutions to quantify and manage geological risk, thus reducing the lost opportunity cost of low-quality geological models and inferior decisions