In well-drilling activities, successful execution of a sequence of operations defined in a well project is critical. To provide proper monitoring, operations executed during drilling procedures are reported in daily drilling reports (DDRs). The complete paper provides an approach using machine-learning and sequence-mining algorithms for predicting and classifying the next operation based on textual descriptions. The general goal is to exploit the rich source of information represented by the DDRs to derive methodologies and tools capable of performing automatic data-analysis procedures and assisting human operators in time-consuming tasks.
Methods
Classification Tasks. fastText. This is a library discussed in the literature designed to learn word embeddings and text classification.
