This paper presents advancements in step-down-test (SDT) interpretation to better design perforation clusters. The methods provided here allow us to better estimate the pressure drop in perforations and near-wellbore tortuosity in hydraulic fracturing treatments. Data is presented from field tests from fracturing stages with different completion architectures across multiple basins including Permian Delaware, Vaca Muerta, Montney, and Utica. The sensitivity of near-wellbore pressure drops and perforation size on stimulation distribution effectiveness in plug-and-perf (PnP) treatments is modeled using a coupled hydraulic fracturing simulator. This advanced analysis of SDT data enables us to improve stimulation distribution effectiveness in multi-cluster or multiple entry completions. This analysis goes much further than the methodology presented in URTeC2019-1141 and additional examples are presented to illustrate its advantages.

In a typical SDT, the injection flowrate is reduced in four or five abrupt decrements or "steps", each with a duration long enough for the rate and pressure to stabilize. The pressure-rate response is used to estimate the magnitude of perforation efficiency and near-wellbore tortuosity. In this paper, two SDTs with clean fluids were conducted in each stage - one before and another after proppant slurry was injected. SDTs were conducted in cemented single-point entry (cSPE) sleeves, which present a unique opportunity to measure only near-wellbore tortuosity using bottom-hole pressure gauge at sleeve depth, negligible perforation pressure drops, and less uncertainty in interpretation. SDTs were conducted in PnP stages in multiple unconventional basins. The results from one set of PnP stages with optic fiber distributed sensing were modeled with a hydraulic fracturing simulator that combines wellbore proppant transport, perforation size growth, near-wellbore pressure drop, and hydraulic fracture propagation.

Past SDT analysis assumed that the pressure drop due to near-wellbore tortuosity is proportional to the flow rate raised to an exponent, β = 0.5, which typically overestimates perforation friction from SDTs. Theoretical derivations show that β is related to the geometry and flow type in the near-wellbore region. Results show that initial β (before proppant slurry) is typically around 0.5, but the final value of β (after proppant slurry) is approximately 1, likely due to the erosion of near-wellbore tortuosity by the proppant slurry. The new methodology incorporates the increase in β due proppant slurry erosion. Hydraulic fracturing modeling, calibrated with optic fiber data, demonstrates that the stimulation distribution effectiveness must consider the interdependence of proppant segregation in the wellbore, perforation erosion, and near-wellbore tortuosity.

An improved methodology is presented to quantify the magnitude of perforation and near-wellbore tortuosity related pressure drops before and after pumping of proppant slurry in typical PnP hydraulic fracture stimulations. The workflow presented here shows how the uncertainties in the magnitude of near-wellbore complexity and perforation size, along with uncertainties in hydraulic fracture propagation parameters, can be incorporated in perforation cluster design.