.min() on a series of NaTs returns nan, while .max() returns NaT
#### Code Sample

```python
s = pd.Series([pd.NaT, pd.NaT])

# Returns nan
s.min()

# Returns NaT
s.max()

```
#### Problem description

Calling `.min()` on an series of `NaT` returns `nan`. I would expect this to return `NaT` to as to keep the type the same. Also, whether it returns `nan` or `NaT`, I would expect it to be consistent with `.max()`. I'm on version `0.22`, not `0.23`, so maybe it was fixed in the latest version, but I didn't see an issue addressing it.

#### Expected Output

I would expect that the `s.min()` call would also return `NaT`.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 45 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: None
pip: 10.0.1
setuptools: 40.2.0
Cython: None
numpy: 1.15.1
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.11
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
