Abstract
The approach to determining the proper benchmark dataset for checking the competitiveness of high complexity wells should involve a systematic definition of the well complexity variables that have a direct impact on the performance of the well.
What makes a well complex and how their competitiveness can be measured against similar wells is a thing of debate. Ranking wells on a universal scale of complexity is itself difficult and controversial as there are several factors that define how complex a well is.
Traditional methods of benchmarking assess the competitiveness of a drilling operation by plotting the performance variable against an independent variable (typically drilled interval). But drilled interval is only one element of complexity.
A few literatures have defined well complexity in terms of the ratio of measured depth to true vertical depth. Other literatures have also recognized factors that impact well complexity such as the type of well profile, kick-off point, long and highly inclined tangent sections, horizontal displacement, water depth, pressure gradients etc. A combination of these factors has been identified to lead to increased complexities in a well. Thus, the ability to measure the competitiveness of extended reach wells has become increasingly difficult.
This paper has been divided into two sections to explore several techniques for defining well complexity and address the challenge with finding the right benchmark dataset to assess the competitiveness of complex wells. Based on the outcome of the analysis, a structured classification of well complexities will be generated for input to benchmarking categorization for high complexity wells. This will thus, enable the prediction of the future performance of wells with higher complexities than conventional wells.
