Development of Reduced Order Modelling Techniques for Downhole Logging Sensor Design

Abstract

Abstract Spectral gamma ray tools provide insights into the mineral composition of formations and such data can be used to distinguish important features of the formation around the wellbore. However, it is a challenge in cased-hole cases to anticipate the attenuation effects of casing within various conditions of density and thickness in an efficient manner. In this work, an innovative reduced- order Monte Carlo modelling technique is presented for cased-hole environment spectrum analysis and, specifically, to numerically determine the attenuation effects of gamma ray transmission through different materials. The presented computational method is developed accounting for different casing and cement thicknesses, and sensor positions within the borehole. The reduced order model construction could be considered one level up from the regular Monte Carlo modelling procedure as it reduces the dimensionality induced by various parameters and therefore proves an extremely useful tool handling large-scale problems that are very common in complicated downhole environment. The adjusted source distributions are then utilized to generate and validate spectra to be applied for difference logging scenarios. Two exemplary field cases are presented: 1. An open-hole logged well; 2. The same set-up well but with steel casing. The reduced modelling techniques are applied to the both cases and the possible impacts of different variable. e.g. borehole size, mud weight and cement thickness on the sensor-obtained spectra are discussed. Future work will involve a series of case studies .e.g. the sensitivity assessment of formation impurities and an extension of the Monte Carlo computed elemental standards to a great variety of nuclear downhole sensor designs.