def xtgeo_well_logs_to_json_format(well: xtgeo.Well) -> List[Dict]:
header = generate_header(well_name=well.name)
curves = []
# Calculate well geometrics if MD log is not provided
if well.mdlogname is None:
well.geometrics()
# Add MD and TVD curves
curves.append(generate_curve(log_name="MD", description="Measured depth"))
curves.append(
generate_curve(log_name="TVD", description="True vertical depth (SS)"))
# Add additonal logs, skipping geometrical logs if calculated
lognames = [
logname for logname in well.lognames
if logname not in ["Q_MDEPTH", "Q_AZI", "Q_INCL", "R_HLEN"]
]
for logname in lognames:
curves.append(generate_curve(log_name=logname.upper()))
# Filter dataframe to only include relevant logs
curve_names = [well.mdlogname, "Z_TVDSS"] + lognames
dframe = well.dataframe[curve_names]
dframe = dframe.reindex(curve_names, axis=1)
return [{
"header": header,
"curves": curves,
"data": dframe.values.tolist()
}]
def get_plotly_zonelog_trace(
well: xtgeo.Well,
zonelog: str,
) -> List[Dict]:
"""Zonetops are extracted from a zonelog and plotted as markers"""
df = well.dataframe
# Find zone transitions
df["transitions"] = df[zonelog].diff()
logrecord = well.get_logrecord(zonelog)
traces = []
for idx in range(0, df.shape[0] - 1):
# Use current sample if moving upwards in stratigraphy
# Use next sample if moving downwards in stratigraphy
if df.iloc[idx + 1]["transitions"] < 0 or df.iloc[idx]["transitions"] > 0:
traces.append(
{
"x": [df.iloc[idx]["R_HLEN"]],
"y": [df.iloc[idx]["Z_TVDSS"]],
"marker": {"size": 10, "color": "red"},
"showlegend": False,
"hoverinfo": "y+name+text",
"text": "TVDSS",
"hoverlabel": {"namelength": -1},
"name": f"Zonetop: <br>{logrecord[df.iloc[idx][zonelog]]}",
}
)
return traces
def wrapper(wellstring, **kwargs):
"""It is currently not possible to initiate from spec.
We work around by dumping to csv before reloading
"""
fpath = "well_data.rmswell"
with open(fpath, "w") as fh:
fh.write(wellstring)
well = Well(fpath, **kwargs)
return well
def make_well_layer(well: xtgeo.Well,
name: str = "well",
zmin: float = 0) -> Dict[str, Any]:
"""Make LayeredMap well polyline"""
well.dataframe = well.dataframe[well.dataframe["Z_TVDSS"] > zmin]
positions = well.dataframe[["X_UTME", "Y_UTMN"]].values
return {
"name":
name,
"checked":
True,
"base_layer":
False,
"data": [{
"type": "polyline",
"color": "black",
"positions": positions,
"tooltip": name,
}],
}
def make_well_layer(well: xtgeo.Well,
name: str = "well",
zmin: float = 0) -> Dict[str, Any]:
"""Make LayeredMap well polyline"""
well.dataframe = well.dataframe[well.dataframe["Z_TVDSS"] > zmin]
positions = well.dataframe[["X_UTME", "Y_UTMN"]].values
return {
"name":
"Well",
"id":
"Well",
"checked":
True,
"baseLayer":
False,
"action":
"update",
"data": [
{
"type": "polyline",
"color": "black",
"positions": positions,
"id": name,
"tooltip": name,
},
{
"type": "circle",
"center": positions[0],
"radius": 60,
"color": "black",
"tooltip": "A",
},
{
"type": "circle",
"center": positions[-1],
"radius": 60,
"color": "black",
"tooltip": "A'",
},
],
}
def append_well_to_data(
data: List[Dict[str, Any]],
well: xtgeo.Well,
wellfile: str,
surface: str,
color: str,
) -> None:
with np.errstate(invalid="ignore"):
surface_picks = well.get_surface_picks(surface)
# get_surface_picks raises warning when MD column is missing in well
if surface_picks is not None:
surface_picks_df = surface_picks.dataframe
coordinates = surface_picks_df[["X_UTME", "Y_UTMN"]].values
for coord in coordinates:
data.append({
"type": "circle",
"center": coord,
"color": color,
"radius": 100,
"tooltip": well.wellname,
"id": wellfile,
})