Taking Charge of a Controllable Variable: Is your perforating gun costing you?

• Across six charge designs evaluated in this study, the charges that deviated the most from their specified perforation diameter also produced the weakest stimulation metrics.

• Meanwhile, charges that tracked closer to their specified perforation diameter consistently delivered stronger stimulation performance.

• Charges B and C averaged only 63% and 56% perforation efficiency, with corresponding UI values of 0.68 and 0.61 – the lowest across all charges evaluated.

• By comparison, charge F delivered 77% perforation efficiency and a UI of 0.84, indicating significantly stronger cluster contribution and stage distribution.

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Side-by-Side Configuration Results

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In a controlled charge comparison where all other perforating system variables were held constant (gun, string configuration, and orientation), a consistent relationship appears between hole size deviation and stimulation performance.

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Charges B and C deviated the most above their specified perforation diameter, producing holes larger than expected. Those same charges showed lower initial perforation friction and weaker limited-entry behavior, which corresponded with the lowest perforation efficiency and cluster uniformity in the dataset.

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Charges F, G, J, and K tracked closer to their specified perforation diameter and delivered noticeably stronger perf efficiency and UI performance.

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Charges B and C averaged only 63% and 56% perforation efficiency, with corresponding UI values of 0.68 and 0.61 – the lowest across all charges evaluated.

By comparison, charge F delivered 77% perforation efficiency and a UI of 0.84, indicating significantly stronger cluster contribution and stage distribution.

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• Charges B and C showed the largest positive deviation from specified EHD (+2.3% and +1.8%).

• Those same charges produced the lowest perforation efficiency and cluster uniformity in the dataset.

• Charges that tracked closer to their specified EHD delivered stronger PE and UI outcomes, indicating more effective cluster contribution.

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The Impact Is Clear

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The impact is clear, field studies show that a 10% increase in Uniformity Index correlates with 7–12% more production in the Williston Basin and 6–10% in the Permian.

Optimizing perforating charges to improve perforation efficiency and cluster uniformity can translate directly into measurable production gains across the well.

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Additionally, if poor perforating charge selection results in only 75% of perforations effectively contributing to stimulation, roughly 25% of the completion investment is not generating productive fracture volume.

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On a $10MM AFE well, that means up to $2.5MM of capital may be deployed without effectively stimulating rock.

Together, these results highlight how charge selection alone can influence stage efficiency and distribution.

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Actionable Next Steps for Program-Level Optimization

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Using measured downhole behavior, this analysis compares charge performance based on perforation efficiency and Uniformity Index rather than nominal charge specifications.

• Use measured perforation efficiency and UI to benchmark charge performance within the same completion design.
• Evaluate charges by how closely actual hole size tracks with designed.
• Standardize the charge designs that deliver the most consistent perforation efficiency and cluster uniformity across wells.

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