Abstract
Summary Woven-metal-mesh sand screens, commonly known as premium screens, have been used extensively by the industry. Sand-retention testing is often executed to evaluate the performance of these screens and to establish empirical guidelines for screen-size selection. These tests are tedious, however, and the results are prone to artifacts and have been used, at best, to correlate trends in sandretention performance with select sand-size-distribution parameters. A new method incorporating results from numerical modeling, in addition to experimental data, is presented to estimate the mass and size distribution of the produced solids in prepack sandretention tests (SRTs) through premium screens. This method provides a fast, reliable correlation to estimate sand production through premium mesh screens when the size distribution of the formation sand is known. This paper presents results from a wide range of pre-pack sand-retention experiments. In these tests, which represent complete hole collapse, the mass of sand produced and its size distribution over time are measured. Results of 3D, discrete- element computer simulations of woven-screen geometry placed in contact with granular sandpacks of approximately 100,000 particles are also presented. On the basis of both the simulations and the experiments, a new method for screen selection is presented. This method is based on a correlation that allows one to use the entire sand-size distribution of the formation sand and to estimate the mass and size distribution of the produced sand. The method is validated by comparisons with experimental data. A new method and new correlations for estimating the mass and size distribution of produced solids in prepack tests through premium screens are presented. Key differences in sand-retention mechanisms between premium screens and wire-wrapped screens (WWSs) have been identified. The method uses the entire-formation sand-size distribution (as opposed to a single design point), and has been validated with laboratory tests. The method also helps in screening anomalous test results.
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