Engineering Gravel Packs for Reliability

Author:

Wassouf Philip1,Jain Samyak1,Kranenburg Aart van2

Affiliation:

1. DuneFront

2. Shell

Abstract

Abstract Sand production is a global problem which causes millions of dollars in equipment damage, deferred or lost production and non-productive time (NPT) every year. Consequently, the accurate selection, modeling and evaluation of sand control techniques is crucial for completion and production optimization as well as risk minimization. This has traditionally been done using spreadsheets, industry rules of thumb and previous experience but, as completions become more complex with longer intervals and smaller fracture pressure windows, error margins are tightening and the cost of failure increasing so a more robust approach is required. This paper details the application of a novel commercially available gravel pack software in the prediction of circulating pressures and gravel placement during the wellbore displacement, step rate test and gravel pack stages of completions operations for two horizontal open hole wells completed with alpha/beta gravel packs. Each well is first simulated to predict expected packing and pressure trends, then evaluated using measured surface and downhole gauge data to identify actual packing mechanisms and better understand downhole events, and finally optimized by directly comparing predicted and measured data to validate model accuracy and reliability. This detailed approach enables the early identification and mitigation of potential risks as well as the ability to better investigate any failures for continuous improvements in both design and operations. Overall, the model is found to match closely with measured data, providing a robust engineering tool for the simulation, evaluation and optimization of horizontal open hole gravel pack (OHGP) completions. The methodology presented facilitates the more accurate design of increasingly complex treatments and helps identify deviations from expected pressure and packing trends to reduce risk, improve reliability and maximize the likelihood of success.

Publisher

SPE

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