Deciphering the Well Complexity Index for Coiled Tubing Interventions, a Unique Factor for Better Engineering and Operational Planning

Abstract

Coiled Tubing (CT) operations complexity has increased exponentially in extended reach developments in the Middle East, and North and South America due to longer horizontals, however rig horsepower (HP) limitations compromise navigation control in the horizontal sections, leading to high tortuosity wells, which hinders CT accessibility. The CT Complexity Index (CTCI) aims to identify critical wells that may require special Extended Reach Tools (ERT), higher Friction Reducer (FR) concentrations, or multiple runs. Computer Assisted Engineering (CAE) software is limited to 500 lines for directional input; hence, this study considers an optimized CT design methodology based on well construction factors to continue using surveys with readings every ∼100 ft. More than 20 well interventions have been analyzed to determine what factors affect the outcome, considering factors such as: Deviation Survey Tortuosity Maximum Dogleg Severity (DLS) Horizontal length 2D or 3D wells Based on statistics, the analyzed results contributed towards developing a CTCI to anticipate possible issues during operations, such as multiple CT runs and the percentage of success in reaching Target Depth (TD). After analyzing data and job results, it was determined that, even though the CAE software shows that TD can be reached, it is possible that multiple runs would be required, or, on some occasions, it would not be possible to reach TD. This is a consequence of multiple factors related to drilling, completion, and CT operations, such as insufficient FR concentration, ERT failure, well tortuosity in the horizontal section, and the fact that the CAE software predicts buckling and CT-completion contact points based on mathematical models which are limited to 500 input lines on the directional survey tab. All of these lead to unaccounted friction forces, where these models can fail to identify some completion contact points affecting the predicted CT reach. Determining a single factor such as CTCI allows the determination ahead of time of either a modified Friction Coefficient (FC) or Paslay Helical Buckling Coefficient (PHBC) to include FR and ERT selection, multiple CT run requirement, or if there is a risk of CT not reaching TD, which in turn can improve job planning. The CTCI can be associated with an adjusted FC or PHBC, allowing more reliable CAE simulation results. The calculation of the CTCI during the planning stage will help to address properly: Technical challenges and solutions to reach TD Forecast operations and coordinate logistic requirements Additional resources (water, additives, BHA) This increases efficiencies and minimizes Non-Productive Time (NPT) related to waiting for resources.