The common downhole drilling hazards which cause NPT are mechanical and differential stuck pipe, string wash out and mud motor failures. Imbalance in downhole pressure leads to kicks and blow out, resulting in loss of asset & equipment, injuries, loss of life & damage to the environment. It also leads to lawsuits and loss of reputation of the operator. Therefore, it becomes imperative that oil and gas companies adopt advanced deep tech technologies to optimize their drilling operations. Technologies such as data analytics, AI, ML, machine vision and video analytics can reduce NPT, ILT and optimize drilling operations.
By suitable application of deep tech technologies, large volume time series data generated during well construction can generate insights into the opportunities related to drilling optimization. Drilling operations are mired with NPT and ILT, which on average is 30 percent of the total well construction time. To reduce NPT, drilling operators can develop AI, ML algorithms which can predict drilling hazards prior to happening of the event. Descriptive analytics can give information on the type and magnitude of inevitable drilling hazard. Prediction of drilling hazard can alert the drilling crew, thereby giving an opportunity to mitigate the down time and NPT. Prescriptive analytics can give suitable suggestions to the driller to mitigate this hazard. Such solutions run standalone, connected to WITSML server storing the time and depth series data of the well. Drilling analytics solution provide real time alerts to operators, drilling crew and third-party teams working in collaboration to perform well construction activities.