This paper further develops an analysis of proppant distribution patterns in hydraulically fractured wells initially presented in SPE-199693-MS. A significantly enlarged database of in-situ perforation erosion measurements provides a more rigorous statistical basis allowing some previously reported trends to be updated, but the main objective of the paper is to present additional insights identified since the original paper was published.

Measurements of the eroded area of individual perforations derived from downhole camera images again provide the input for this study. Entry hole enlargement during limited entry hydraulic fracturing provides strong and direct evidence that proppant was successfully placed into individual perforations. This provides a straightforward evaluation of cluster efficiency. Perhaps more importantly the volume of proppant placed into a perforation can also be inferred from the degree of erosion. Summing individual perforation erosion at cluster level allows patterns and biases to be identified and an understanding of proppant distribution across stages has been developed.

Outcomes from an analysis of a database that now exceeds 50,000 eroded perforations are presented. Uniform reservoir stimulation is a key objective of fracture treatments but remains challenging to measure and report. The study therefore focused on understanding how uniformly proppant is distributed across more than 1,800 measured stages.

Results demonstrate how proppant distribution within stages is influenced when treatment parameters change. Our approach was to vary one parameter, for example the stage length, while all other parameters were maintained at a consistent value. We investigated multiple parameters that can be readily controlled during treatment design and show how these can be manipulated to improve proppant distribution. These included stage length, cluster spacing, perforation count per cluster and perforation phase.

Hydraulic fracturing is a complex, high energy process with numerous input parameters. At individual cluster and stage level outcomes can be unpredictable and diagnostic results are often quite variable. The approach taken here was to complete a statistical analysis of a sufficiently large dataset of in-situ measurements. This allowed common trends and patterns to be confidently identified and conclusions reached on how proppant distribution is affected by varying specific design parameters. This should be of interest and value to those designing hydraulic fracture treatments.

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