Pumping multiple unique stimulation designs in a single multistage lateral combined with particulate oil-soluble tracer chemicals (OSTs) accelerates the traditional trial and error process of optimizing stimulation designs. Applying this methodology to various fracturing sand volumes provides discrete data for stimulation analysis. When compared to a large sample of wells, the data shows that OST tracer recovery may be used as a proxy to estimate oil production.

Altering fracture designs within the same wellbore with OSTs provides significant data that is useful for optimizing stimulation designs. Solid particulate OSTs differ from liquid OSTs in that the particulates remain locked in-situ in the proppant pack after the frac pressure wave has subsided. Formation pressure will not force the solid tracer back into the wellbore as sometimes occurs with liquid tracers. The unique chemistry of OSTs allows the tracing chemicals to dissolve only into produced oil, which is sampled at the surface for laboratory analysis.

Multi-stage lateral wells utilizing alternating stimulation designs with unique OSTs yield data suggesting increased proppant volumes lead to larger oil recoveries compared to lower proppant volumes. Ninety-four horizontal wells within the same bench of the Wolfcamp formation with various proppant volumes show a statistically significant correlation between proppant volumes and estimated ultimate recoveries (EURs). The OST recovery results closely match the trend of the 94 full-well completions, giving evidence that OST recoveries are a quantitative analogy for oil production over time. Increased proppant loading OST tests, beyond the range of full-well data available, show no gain in OST recovery. This suggests that adding more proppant in this specific portion of the reservoir may not add economic value to the operator.

The unique ability of OSTs to generate granular information at the individual stage level accelerates an operator's learning curve as optimizing stimulation design often requires costly investments in reservoir information. Another approach is to optimize stimulation design using empirical data if wells in a similar geological and petrophysical makeup exist. The OST alternating-stage-design methodology can be applied to other variables, providing a rapid trial-and-error process that yields significant empirical data for optimizing completion variables.

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