This answer is a bit messy, but it should work...
If we have access to a fully homomorphic encryption scheme $E(x)$ then we know that $E(x) + E(y) = E(x+y)$ and $E(x) \cdot E(y) = E(x \cdot y)$.
In addition we know that there exists an efficient Boolean circuit, $BC$, such that $BC(x_1,x_2,...,x_n) = y_1, y_2,...y_n$ where $x_i$ and $y_i$ are the bits of the binary string $x$ and $y$ respectively both of length $n$ and that $x = b^y$ for some base $b$. Thus this is the circuit for $\log_b(x) = y$.
Now instead of being given $E(x)$ we can just as easily be given $E(x_1), E(x_2), ..., E(x_n)$. When you want to encode a $0$ you map it to a random even number, $b$, then you encrypt that number, $E(b)$. Likewise for $1$, except you map it to an even number. Now all we do is evaluate the circuit and when we encounter an xor gate we do $E(I_1 \oplus I_2) = E(I_1) + E(I_2)$ and likewise for and gates $E(I_1 \wedge I_2) = E(I_1) \cdot E(I_2)$ where $I_1$ and $I_2$ are the inputs to the gate. For all other gates convert them into $and$ and $xor$ gates. At the end we will be left with $E(y_1), E(y_2),...,E(y_n)$ which is an encryption of the $\log_b(x)$.
One interesting benefit is that $x$ and $y$ could be represented in any way, not just a n-bit integer. You would just need to use the correct circuit for the representation. For example if $n = 64$ you could let $x_1,x_2,...,x_n$ be the IEEE 754 double-precision binary floating-point format representation of $x$ and with the correct circuit $y_1, y_2,...y_n$ would be a double-precision floating-point so you can do more precise calculations if you wanted.
See What does "circuits" mean in Cryptography? for more details on the Boolean circuit only using addition and multiplication.
Edit:
Since the question originally asked how to get from $E(x)$ to $E(log(x))$ and my answer only works if you have the bits and returns bits, I asked another question Fully Homomorphic Encryption: Going from an integer to bits to try to help.
They suggested using a Bit Extraction Circuit to go from $E(x)$ to $E(x_1), E(x_2), ..., E(x_n)$. Then compute the above. Now you have $E(y_1), E(y_2),...,E(y_n)$ which you can easily put back together by computing (assuming $y_1$ is the least significant bit) $E(log(x)) = E(y_1) + 2\cdot E(y_2) + 2^2\cdot E(y_3)+\dots+2^{n-1}\cdot E(y_n)$