This is a lognormal probability plot labeled with percentages rather than lognormal quantiles.
Specifically, let the ordered data be written $x_1 \le x_2 \le \cdots \le x_n$ and let $\Phi$ be the standard Normal cumulative distribution function. Form a parallel sequence of plotting points corresponding to percentages of the data; a convenient and simple rule is to associate $p_i = \frac{i-1/2}{n}$ with $x_i$. Make a scatterplot of these data via the ordered pairs
$$\left(\log(x_i), \Phi^{-1}(p_i)\right)$$
Label the x-axis with the values of the $x_i$ (not their logarithms) and label the y-axis with the values of the $p_i$ (not their Normal quantiles).
In R, qqnorm almost accomplishes all of this, except it labels the y-axis with the Normal quantiles. You can supply custom labels if you like:
x <- exp(rnorm(500)) # Sample data
qqnorm(x, datax=TRUE, log="x") # Probability plot with a logarithmic data axis
percents <- c(0.001, 0.025, 0.165, 0.500, 0.835, 0.975, 0.999)
mtext(as.character(percents), side=4, at=qnorm(percents), cex=0.8)
