As unconventional resource plays are developed, they transition to early ‘Green Field’ phase projects that require large amounts of data for validation, evaluation, and characterization. The ‘Gold Field’ stage of development attempts to optimize efficiency and maximize asset value. Drilling strives to be more repeatable as processes are honed to minimize time from spud to completion. Data acquisition is often sacrificed toward these goals. Well performance becomes statistical with both under and over achievers distributed in the mix. Due to limited data acquisition, it is harder to be predictive on well performance and EUR. During the ‘Brown Field' stage of development the main objective is to extend the life of the declining asset. The desire to get more from the reservoir while minimizing expenses leaves data acquisition a low priority in lieu of controlling expenses. Attempts at using well analytics to describe well performance have varying success since there are so many variables that impact performance such as reservoir quality, heterogeneity, and completion design. Other issues of unexpected well performance arise and are tough to isolate and identify since there is little or no analytic data to pinpoint the responsible factors.

This paper presents examples from the middle member of the Bakken formation in North Dakota as well as the Eagle Ford shale in Texas. These examples will demonstrate the variation and heterogeneity of resource plays across a fairly small area and the necessity to identify the contributing factors of this variation to completing wells employing this knowledge. Five different approaches for well analysis and completion design are highlighted in this paper. Cemented liner completions with ‘Plug and Perf’ completions are used as a standard through these examples to best isolate and identify zones of like stresses for completion designs. Each of the approaches will be discussed reviewing their relative Pros and Cons and lead to the conclusion that recognition of the reservoir characterization variability and quality should lead to better completion methods that maximize well performance and EUR.

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