odbind.well

Module Contents

Classes

Well	A class for an OpendTect Well

class odbind.well.Well(survey: Survey, name: str)

Bases: odbind.survey._SurveyObject

A class for an OpendTect Well

property log_names: list[str]

list[str]: Names of well logs in this well (readonly)

property marker_names: list[str]

list[str]: Names of well logs in this well (readonly)

classmethod _initbindings(bindnm)

log_info(forlognms: list[str] = []) → dict

Return basic information for all or a subset of logs in this well.

Parameters

forlognmslist[str]=[]

(Optional) a list of log names to use. For an empty list information for all logs in the well is provided.

Returns

dict

log_info_dataframe(forlognms: list = []) → dict

Return basic information for all or a subset of logs in this well as a Pandas DataFrame.

Parameters

forlognmslist[str]=[]

(Optional) a list of log names to use. For an empty list information for all logs in the well is provided.

Returns

Pandas Dataframe

marker_info(formarkernms: list[str] = []) → dict

Return basic information for all or a subset of markers in this well.

Parameters

formarkernmslist[str]=[]

(Optional) a list of marker names to use. For an empty list information for all markers in the well is provided.

Returns

dict

marker_info_dataframe(formarkernms: list[str] = []) → dict

Return basic information for all or a subset of markers in this well as a Pandas DataFrame.

Parameters

formarkernmslist[str]=[]

(Optional) a list of marker names to use. For an empty list information for all markers in the well is provided.

Returns

Pandas Dataframe

track()

Return dict of numpy arrays with the well track.

Returns

dict

track_dataframe()

Return the well track as a Pandas DataFrame .

Returns

Pandas DataFrame

logs(lognms: list[str] = [], zstep: float = 0.5, upscale: bool = True)

Return dict of numpy arrays for all or a subset of logs in this well

Parameters

lognmslist[str] = []

list of log names or empty list for all

zstepfloat = 0.5

(Optional) output sampling step in the surveys default depth unit

upscalebool = True

(Optional) if True log is resampled by averaging over the step, otherwise use linear interpolation

Returns

dict[np.arrays] keyed by the log names, ‘dah’ is the depth log list[str] of the log unit of measures, there is one entry in the list for each array in the dict

logs_dataframe(lognms: list[str] = [], zstep: float = 0.5, upscale: bool = True)

Return all or a subset of logs in this well as a Pandas DataFrame

Parameters

lognmslist[str] = []

list of log names or empty list for all

zstepfloat = 0.5

(Optional) output sampling step in the surveys default depth unit

upscalebool = True

(Optional) if True log is resampled by averaging over the step, otherwise use linear interpolation

Returns

Pandas DataFrame

put_log(lognm: str, dah: numpy.ndarray, logdata: numpy.ndarray, uom: str = None, mnem: str = None, overwrite: bool = False)

Add a log curve to this well

Parameters

lognmstr

the name for the new log

dahnp.ndarray

1D float32 numpy array with the depth-along-hole (MD) of the logdata in the survey’s default depth unit

logdatanp.ndarray

1D float32 numpy array with the log data

uomstr

the unit of measure of the new log

mnemstr

the Mnemonic of the new log

overwritebool=False

whether to overwrite if lognm already exists in the well

delete_logs(lognms: list[str] = [])

Delete the listed log names from the well

Parameters

lognmslist[str]

list of log names to be deleted

Returns

bool : True/False indicating success/failure

tvdss(dah: float)

Return TVDSS for a MD/dah depth, all in the survey’s default depth unit

tvd(dah: float)

Return a TVD for a MD/dah depth, all in the survey’s default depth unit

static common_markers(survey: odbind.survey.Survey, forwells: list[str] = [])

Return list of markers common to the listed wells or all wells in the survey

Parameters

surveySurvey

the OpendTect survey object

forwellslist[str]

list of well names to consider

Returns