Measurement error models on lognormal distributed data

I would love to be wrong but I don’t think there is a way around the fact that you lack the weight of the envelope before drying…

Your goal is to relate dry mass to some predictors, presumably. Even if you get around the "Error: Family ‘lognormal’ requires response greater than 0.” your error is not measured per observation; it is a distribution of weights of the used envelopes, but it is disconnected from any given observation. See also this discussion.