Data I/O

Well Log

Well logs for a single well are stored internally as pandas DataFrame.

Both Standard LAS file and Pseudo-LAS file (TSV file without LAS header)

Seismic Velocity

When it comes to 3D seismic data, we directly interact with SEGY file utlizing segyio.

SeiSEGY.__init__(segy_file, like=None)

Parameters

• segy_file (str) – segy file path

• like (str, optional) – created segy file has the same dimesions as like.

class pygeopressure.basic.seisegy.SeiSEGY(segy_file, like=None)

cdp(cdp)

data of a cdp

crline(crline)

data of a crossline section

crlines()

Iterator for crline numbers

Yields

int – cross-line number

data(indexes)

Retrieve Data according to the index provided.

Parameters

indexes ({InlineIndex, CrlineIndex, DepthIndex, CdpIndex}) – index of data to retrieve

Returns

Return type

numpy.ndarray

depth(depth)

data of a depth slice

depths()

Iterator for z coordinate

Yields

float – depth value

classmethod from_json(json_file, segy_file=None)

Initialize SeiSEGY from an json file containing information

Parameters

• json_file (str) – json file path

• segy_file (str) – segy file path for overriding information in json file.

inline(inline)

data of a inline section

inline_crlines()

Iterator for both inline and crline numbers

Yields

tuple of int – (inline number, crossline number)

inlines()

Iterator for inline numbers

Yields

int – inline number

plot(index, ax, kind='vawt', cm='seismic', ptype='seis')

Plot seismic section according to index provided.

Parameters

• index ({InlineIndex, CrlineIndex, DepthIndex, CdpIndex}) – index of data to plot

• ax (matplotlib.axes._subplots.AxesSubplot) – axis to plot on

• kind ({‘vawt’, ‘img’}) – ‘vawt’ for variable area wiggle trace plot ‘img’ for variable density plot

• cm (str) – colormap for plotting

• ptype (str, optional) – property type

Returns

Return type

matplotlib.image.AxesImage

update(index, data)

Update data with ndarray

Parameters

• index (InlineIndex)

• data (2-d ndarray) – data for updating Inline

valid_cdp(cdp_num)

Return valid CDP numbers nearest to cdp_num