The desired integral can be wrestled into submission by brute-force manipulations; here, we instead try to give an alternative derivation with a slightly more probabilistic flavor.
Let $X \sim \mathrm{Exp}(k,\lambda)$ be a noncentral exponential random variable with location parameter $k > 0$ and rate parameter $\lambda$. Then $X = Z + k$ where $Z \sim \mathrm{Exp}(\lambda)$.
Note that $\log(X/k) \geq 0$ and so, using a standard fact for computing the expectation of nonnegative random variables,
$$
\newcommand{\e}{\mathbb E}\newcommand{\rd}{\mathrm d}\renewcommand{\Pr}{\mathbb P}
\e \log(X/k) = \int_0^\infty \Pr(\log(X/k) > z)\,\rd z = \int_0^\infty \Pr(Z > k(e^z - 1)) \,\rd z \>.
$$
But, $\Pr(Z > k(e^z -1)) = \exp(-\lambda k(e^z - 1))$ on $z \geq 0$ since $Z \sim \mathrm{Exp}(\lambda)$ and so
$$
\e \log(X/k) = e^{\lambda k} \int_0^\infty \exp(-\lambda k e^z) \, \rd z = e^{\lambda k} \int_{\lambda k}^\infty t^{-1} e^{-t} \,\rd t \>,
$$
where the last equality follows from the substitution $t = \lambda k e^z$, noting that $\rd z = \rd t / t$.
The integral on the right-hand size of the last display is just $\Gamma(0,\lambda k)$ by definition and so
$$
\e \log X = e^{\lambda k} \Gamma(0,\lambda k) + \log k \>,
$$
as confirmed by @Procrastinator's Mathematica computation in the comments to the question.
NB: The equivalent notation $\mathrm E_1(x)$ is also often used in place of $\Gamma(0,x)$.
Assumptions
for specifying the parameter space. $\endgroup$Integrate[Log[x + k]*\[Lambda]*Exp[-\[Lambda]*x], {x, 0, \[Infinity]}, Assumptions -> k > 0 && \[Lambda] > 0]
. You can just copy it and paste it on a .nb file. I am not sure if the Wolfram Alpha allows for including restrictions. $\endgroup$