Stuck pipe prediction from rare events in oil drilling operations
Year: 2023
Type: article
Abstract: Stuck-pipe phenomena are relatively rare in drilling operations in the oil & gas industry, but can have disastrous economic consequences, causing costly time delays and sometimes even the loss of expensive machinery. In this work, we develop an event-based prediction model that relates the occurrence of precursor events to the stuck-pipe phenomena. To this aim, the detectors of various types of precursor events that typically anticipate stuck-pipe occurrences are first designed based on the available mudlog data. A Hidden Markov Model (HMM) is then developed to relate these precursor events to actual drilling problems, producing different levels of alarm, with the ultimate goal of predicting stuck pipes. The model has been tested on a dataset of wells with different characteristics, showing positive results.
Source: Upstream Oil and Gas Technology
Institutions: Politecnico di Milano, Eni (Italy)
Language: English
Subfield: Fuel Technology
Field: Energy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,060
OpenAlex ID: W4385757261