Early detection and quantification of gas kicks during drilling and completions is essential to proper well control and in the prevention of blowouts. The utilization of distributed sensing techniques, acoustic (DAS) and temperature (DTS), enables real-time elucidation of these multiphase flow events. Identifying and validating event signatures (fingerprinting) in these sensing technologies is crucial to informing operators of how to interpret these data streams. Performing full-scale analysis allows these events to be properly characterized, given the complexities in the fluid mechanics and gas dynamics.

This project utilizes a 9-5/8 inch and 5200 foot deep wellbore at the LSU PERTT Laboratory retrofit with distributed fiber optics (DAS and DTS) and 4 permanent pressure-temperature gauges to sense and visualize gas kick dynamics downhole in real time. Several experiments were performed involving the injection of nitrogen kicks through a chemical injection line and also by bullheading down 2-7/8 inch tubing in both stagnant and circulating water. Variations in flow rate, kick size, and backpressure are investigated including gas migration during shut-in. DTS and DAS data are collected downhole, along with gauge pressure and temperature at four depths along the wellbore. Data is consolidated with the rig recorded surface data to create a complete picture of the experiments.

Several observations are possible with this new methodology. First, the gas kick is immediately visible (audible) entering the wellbore by the sensors and the gas front was traceable in real time as it rose to the surface, allowing for detection of a kick, improved estimation of kick size, and easy calculation of rise velocity. Second, the distribution of gas axially in the wellbore was visible and provided insights into the duration of the event. Third, the compressibility dynamics can be visualized with the DAS thus elucidating details of bubble and slugging sizes and dynamics and when discrete gas has completely circulated out of the wellbore. The frequency ban filtering of the data further augments the fidelity of gas bubble sizes and dynamics. These initial results provide a proof of concept for using downhole sensing for real time riser gas dynamic detection and characterization.

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