Exploration Drilling Management System Based on Digital Twins Technology

Abstract

Digital transformation of oil and gas companies requires consistent improvement of work performance management. Oil and gas companies strive to improve work efficiency and consistently develop and implement digital products. The realization of such complicated solutions requires deep diving into current business processes and transformation of them. This paper deals with implementation of digital management system for exploration and production wells. Digital management system for exploration and production wells is based on ideology of digital twin and act as a single window and single source of data for all exploration and production wells. Digital management system covers whole construction process started from planning stage to execution and results assessment and orchestrates the exchange of data between process phases and people involved in it. Transparency provided by the digital twin improves efficiency and accelerates well construction process. Cognitive assistants based on AI and ML techniques are implemented at every stage: while planning, the assistants search analogue wells, analyze its design and complications while drilling and provide recommendations for the most optimal well design, offers the optimum drilling mud density and recommends the most suitable set of logs to cover geological section uncertainty. At the execution stage, a number of ML assistants are used to increase efficiency and reduce risks while drilling: automatic method for anomaly detection while drilling to prevent complications while drilling, machine learning based model for automatic torque and drag control to control borehole condition to predict any signs of differential stuck, key sitting and pack-off, data-driven model for drilling bit position and direction determination to predict BHA position while drilling including a blind zone, data-driven model for the identification of the rock type at a drilling bit for correct geosteering application.