  WL measurements have well-known shear estimation biases, which can be
partially corrected for with the use of image simulations. We present an
analysis of simulated images that mimic HST/ACS observations of high-redshift
galaxy clusters, including cluster specific issues such as non-weak shear and
increased blending. Our synthetic galaxies have been generated to match the
observed properties of the background-selected samples in the real images.
First, we used simulations with galaxies on a grid to determine a revised
signal-to-noise-dependent correction for multiplicative shear measurement bias,
and to quantify the sensitivity of our bias calibration to mismatches of galaxy
or PSF properties between the real data and the simulations. We studied the
impact of increased blending and light contamination from cluster and
foreground galaxies, finding it negligible for $z>0.7$ clusters, whereas there
is an effect at the $\sim 1\%$ level for lower redshift clusters. Finally, we
studied the impact of fainter neighbours and selection bias mimicking the
positions and magnitudes of galaxies in CANDELS data. The initial SExtractor
object detection causes a selection bias of $-0.028 \pm 0.002$, reduced to
$-0.016 \pm 0.002$ by further cuts. We compared our CANDELS-based estimate to a
grid-based analysis, with added clustered galaxies reaching even fainter
magnitudes, yielding a refined estimate of $\sim -0.013$. Our pipeline is
calibrated to an accuracy of $\sim 0.015$, which is fully sufficient for
current and near-future weak lensing studies of high-redshift clusters. As an
application, we used it for a refined analysis of three highly relaxed clusters
from the SPT-SZ survey, including measurements down to $r>200$ kpc. Compared to
previously employed scales, this tightens the cluster mass constraints by a
factor 1.38 on average.
