Realistic Assessment of Proppant Pack Conductivity for Material Selection

Abstract

Abstract Proppant selection in hydraulic fracturing is a critical economic and technical decision that affects stimulation and field development economics. In many cases the selection is based on laboratory data from standardized API conductivity tests on clean packs at specified stress and temperature. These tests predict conductivities that are optimistic compared to observed field performance. Often a laboratory measured conductivity difference of only 5–10% is considered a significant variance when applied to the producing life of a well. The significance of these small differences, however, is often overwhelmed by other factors affecting fracture performance in the field. The selection of a particular proppant should be based on an identifiable difference in performance under field conditions. This requires an accurate assessment of all the damage mechanisms that can and do occur during fracturing and their impact on final conductivity. This paper outlines the primary damage mechanisms and their effect on conductivity, fracture cleanup and ultimate stimulation response. The expected variance in laboratory measurements of conductivity is also quantified. Introduction In hydraulic fracture treatment design one of the most important decisions is which proppant to use. The choice of proppant also directly impacts overall job economics, treatment size, and the ultimate productivity of the well. The decision is commonly driven by balancing effective fracture length and conductivity against reservoir flow capacity, as in the McGuire-Sikora folds-of-increase curves, or through estimates of dimensionless fracture flow capacity (FCD).1 Any of these methods require an accurate assessment of proppant pack conductivity under reservoir flow conditions along with knowledge of reservoir deliverability. Frequently the proppant pack conductivity is estimated from standardized API conductivity tests of proppants in a linear flow cell at a specified pack concentration, closure stress, and temperature. The impact of time at stress, rate of stress application, and other factors that affect these "baseline" conductivity tests has been documented.2 One aspect of these tests that has not been well documented is the expected statistical variation in laboratory results when all tests are conducted as similarly as possible in terms of cell loading, stress application, aging at stress, fluid compatibility, and flowing conditions. The choice of a particular proppant, based on superior performance characteristics, requires that the performance of two different materials be statistically significant. This paper addresses the statistical variance in laboratory conductivity measurements on similar proppant samples at similar stress, temperature, and flow conditions. In this case "similar" means as close to the same as can be determined in the lab. Beyond the reproducibility of laboratory measurements, some of the principal mechanisms affecting final proppant-pack conductivity are addressed. Specifically these include:Non-Darcy flow: What is the velocity distribution in the fracture and how does it affect conductivity loss?Multiphase flow: What does the two- and three-phase relative permeability curve for a proppant pack look like, can it be measured, and how important is it?Multiphase non-Darcy flow: How does multiphase flow in the proppant pack change ß, velocity, apparent flowing density, and viscosity? What is the effect on final conductivity?Gravity and viscous segregation: Do we really know what the flow path is in a proppant pack, how much cleans up, and what the local velocity is? How does this affect conductivity?Reservoir flow capacity: Does the reservoir determine the amount of conductivity required? Is there ever "too much"?