Lognormal Distribution
Let \(X\sim Lognormal(\mu, \sigma^2)\)
Then \(log(X)\sim Normal(\mu, \sigma^2)\)
Let \(m\) and \(s\) denote the mean and standard deviation of X. Let \(c=s/m\) denote the CoV.
We have
\[\begin{align*} m & = e^{\mu + \sigma^2/2} \\ s^2 & = m^2\left(e^{\sigma^2}-1\right) \end{align*}\]Therefore if you started with \(m\) and \(s\) you could calculate the underlying normal parameters thus
\[\sigma^2 = log(1+c^2)\] \[\mu = log(m)-\sigma^2/2 = log\left(\frac{m}{\sqrt{1+c^2}}\right) = log\left(\frac{m^2}{\sqrt{m^2+s^2}}\right)\]