An Integrated Approach to the Design and Modelling of High Rate Water Pack Treatments

Abstract

High Rate Water Pack (HRWP) treatments are used in cased hole gravel packs with the intention of creating small fractures to bypass near wellbore damage and improve perforation packing. Despite their popularity as a sand control technique, there has never been a software model developed specifically for HRWP treatments, and so their design has been largely driven by trial-and-error based on local field experience. Often, local field experience is insufficient to achieve the desired results due to uncertainties in the fracture initiation, propagation and packing mechanisms. The ability to model the initiation and packing of the fracture provides a better understanding of the achievable perforation packing in a specific well and how to maximize it. Such a model must simultaneously simulate fluid hydraulics, wellbore packing, fracture initiation and propagation, and gravel placement. Models exist for gravel packing that can predict packing in the wellbore annulus and perforations, but they do not account for initiation, propagation and packing of the fractures. Multiple models are also available specifically for fracturing design, but most of these do not account for wellbore packing. These models are more suited for conventional hydraulic fracturing and frac pack treatments using highly viscous or crosslinked fluids. Such fracturing models tend to overpredict fluid leak-off in soft rock formations, especially with low viscosity fluids, and consequently predict premature screen-outs under conditions in which HRWP treatments are in practice successfully placed. This paper introduces the first software model that combines both wellbore and perforation packing, along with the initiation and packing of small fractures, to facilitate successful HRWP treatments. Examples of how the model can be used to optimize HRWP treatments are discussed and the various parameters that impact HRWP design are also assessed. Several case studies are presented comparing modelled and actual data to both validate the model and demonstrate how it can be used to optimize the designs for offset wells.