Using Integrated Computational Materials Engineering for Oil and Gas Applications

Abstract

Abstract Integrated Computational Materials Engineering (ICME) is an approach to materials design, optimization, and insertion as well as solving challenges on implementation and selection of existing materials using a combination of physics-based modeling and machine learning methods. In the present work QuesTek will demonstrate how ICME can be used to improve mechanical properties, corrosion properties, and processability of common structural materials used in oil country tubular goods (OCTG). This work uses QuesTek's ICMD® software platform including thermodynamics- and kinetics-based databases and modeling as well as physics-based analytical modeling and simulation approaches to predict process-structure-property relationships in structural alloys. Using these predictive modeling tools, the composition and processing are optimized to achieve improved performance. QuesTek will demonstrate results of composition and heat treatment optimization on mechanical and corrosion properties. Specifically, stress-corrosion cracking susceptibility and strength of alloys was explored and the sensitivity within specification ranges was examined. The results showed that these methods can be used to tighten specification ranges and adjust heat treatments to improve robustness of material performance for a given application. Integrated computational materials engineering (ICME) is a relatively new approach to materials engineering which leverages the many advancements in both physics-based modeling and computational speed over the last couple of decades. The materials genome initiative has pushed for the utilization of ICME to improve novel materials design and development as well as improving alloy optimization, qualification, and troubleshooting of materials challenges for insertion of existing materials into new applications. This methodology has been growing in use in many industries (e.g., aerospace, space, defense, biomedical, automotive, nuclear, etc.) but its use in the Petroleum industry is still relatively limited. This work outlines how this approach could be adopted for practical oil and gas applications, and what the benefits would be.