The full text of this item is not available at this time because the student has placed this item under an embargo for a period of time. The Libraries are not authorized to provide a copy of this work during the embargo period, even for Texas A&M users with NetID.
Developing Leading Indicators Framework for Predicting Kicks and Preventing Blowouts
MetadataShow full item record
Due to the operational complexities of drilling, completion and well intervention activities, it is often quite challenging to predict a potential blowout scenario timely and efficiently. In drilling operations, blowouts are usually preceded by kicks and predicting kicks early is crucial for regaining control of the well and preventing major incident. Kicks and blowouts happen due to failure of well control barriers and leading indicators could be very effective in identify vulnerabilities in such systems. For assessing integrity of well control barriers with appropriate sets of leading indicators, a robust framework was proposed and sets of probabilistic models were developed in this work. By following a systematic cause-based methodology proposed in this work, sets of leading indicators were identified for monitoring barrier performances while drilling, completion and well intervention activities. Analyses of Montara and Deepwater Horizon blowout incidents demonstrated applicability of leading indicators framework in revealing system weaknesses prior to major incidents. Using the real-time kick indicators, decision support algorithms were developed in this work which would help to understand a kick progression scenario and actions required to confirm a kick. Leading indicators-based probabilistic models were developed for evaluating the relative importance of different organizational and operational factors, and assessing their impacts on the key causal factors of well control barrier failure events. These models were constructed for hydrostatic head failure events which can be caused by abnormal pore pressure and swabbing, and cementing failure during drilling and completion activities. An integrated iii model for assessing well control failure events during wireline operations was also constructed. These models represent realistic scenario of barrier health and could be very useful for determining barrier failure probabilities from observed data. Addition to these, efficiencies of kick detection parameters to detect potential influxes and factors impacting their performances can also be assessed with the developed models. These functions enable informed decision-making for preventing kicks and blowouts while drilling or intervening a well, by providing real-time status of the well control system.
Tamim, Md Nafiz Ekram (2019). Developing Leading Indicators Framework for Predicting Kicks and Preventing Blowouts. Doctoral dissertation, Texas A & M University. Available electronically from