Optimizing Drillouts Using Live TFA

Author:

Kuhlman Luke Ray1,Thomas Travis Gideon2,Pursell John Carlton2,Buck Noah Anderson2,Scherer Kayla Renee2

Affiliation:

1. KLX Energy Services

2. NOV Inc.

Abstract

Abstract This paper examines how real-time force monitoring keeps operations on path by decreasing operational failures (such as stuck or parted pipe), reducing non-productive time (NPT), and increasing drillout efficiency (hour/plug). Utilizing interactive tubing force analysis (TFA) models with real-time data overlays provides coiled tubing operators with the data needed to reduce stuck pipe events, increase drillout efficiencies, and decrease mechanical failures (both on the surface and downhole). The key to optimizing efficiencies is maintaining consistent data that can be analyzed with the TFA. One current challenge is that analyzed data can only affect future operations if engineering controls are executed in the field. By using the interactive TFA and real-time operational data synchronously, users can positively impact their current and future operations by using data-driven decisions instead of predetermined processes. By implementing a cloud-based application in conjunction with software that acquires and stores field data, one field-based end user recognized real-time divergence from the modeled parameters. This is a key indicator of potential failures. The application allows for on-the-fly procedural corrections (such as stop and circulate) to alleviate operational risk for stuck pipe instances. In one case, the application indicated forewarned risk while running in hole that would have saved the service company and Exploration and Production (E&P) company more than 48 hours in NPT. Having cloud-connected software with pre-defined warnings provides the field, management, and engineering staff with real-time access to the same data, allowing quick and inclusive decisions to be made prior to potential failures. Without this implementation, only post-job analysis would have revealed the divergence of the field data from the predictive data. The live feed of operational data provided by the application prevented stuck pipe scenarios when well conditions changed. Personnel could not have made this prediction if the coiled tubing (CT) operator was relying solely on the pre-defined job scope and pre-job planning procedures. This paper expands on previous documentation where the TFA and real-time data were manually overlaid to significantly reduce an E&P's risk. This novel refinement of technology coalesces essential information to create a holistic view of operations thereby preventing issues rather than analyzing them after the fact.

Publisher

SPE

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