def load_wells():
base_dir = "./data/McMurray_data"
# # load well data
"""Need to add a method for the user to point to the directory or add additional las files later"""
fpath = Path(base_dir+"/las/*.LAS")
return Project.from_las(str(fpath))
def test_project():
"""
Test basic stuff.
"""
project = Project.from_las('tests/1.las')
assert len(project) == 1
w = Well.from_las('tests/2.las')
project += w
assert w in project
assert len(project) == 2
project += project
assert project.uwis[0] == '1'
s = "<table>"
s += "<tr><th>Index</th><th>UWI</th><th>Data</th><th>Curves</th></tr>"
s += "<tr><td>0</td><td><strong>1</strong></td>"
assert s in project._repr_html_()
# Check __getitem__.
assert project[1] == w
assert len(project[:2]) == 2
l = [0, 1]
assert len(project[l]) == 2
assert len(project.get_mnemonics(['DT'])) == 4
html = project.curve_table_html()
assert '<table><tr><th>Idx</th><th>UWI</th><th>Data</th><th>Passing</th>' in html
assert "<th>DPHI_SAN</th>" in html
s = """<td style="background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;">DTS"""
assert s in html
def test_project():
"""
Test basic stuff.
"""
project = Project.from_las('tests/1.las')
assert len(project) == 1
w = Well.from_las('tests/2.las')
project += w
assert w in project
assert len(project) == 2
project += project
assert project.uwis[0] == 1
s = "<table><tr><th>UWI</th><th>Data</th><th>Curves</th></tr><tr><td>1</td>"
assert s in project._repr_html_()
# Check __getitem__.
assert project[1] == w
assert len(project[:2]) == 2
l = [0, 1]
assert len(project[l]) == 2
assert len(project.get_mnemonics(['DT'])) == 4
html = project.curve_table_html()
assert '<table><tr><th>Idx</th><th>UWI</th><th>Data</th><th>Quality</th>' in html
assert "<th>DPHI_SAN</th>" in html
s = """<td style="background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;">DTS"""
assert s in html
def test_project():
"""
Test basic stuff.
"""
project = Project.from_las('tests/1.las')
assert len(project) == 1
w = Well.from_las('tests/2.las')
project += w
assert w in project
assert len(project) == 2
project += project
assert project.uwis[0] == 1
s = "<table><tr><th>UWI</th><th>Data</th><th>Curves</th></tr><tr><td>1</td>"
assert s in project._repr_html_()
# Check __getitem__.
assert project[1] == w
assert len(project[:2]) == 2
l = [0, 1]
assert len(project[l]) == 2
assert len(project.get_mnemonics(['DT'])) == 4
html = project.curve_table_html()
assert "<table><tr><th>UWI</th><th>Data</th>" in html
assert "<th>DPHI_SAN</th>" in html
s = """<td style="background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;">DTS<div style="font-size:80%; float:right; padding:4px 0px 4px 6px; color:#CCCCCC;"></div><br /><span style="font-size:70%; color:#33AA33">us/ft</span></td>"""
assert s in html
def test_project():
"""
Test basic stuff.
"""
project = Project.from_las('tests/1.las')
assert len(project) == 1
w = Well.from_las('tests/2.las')
project += w
assert w in project
assert len(project) == 2
project += project
assert project.uwis[0] == 1
s = "<table><tr><th>UWI</th><th>Data</th><th>Curves</th></tr><tr><td>1</td>"
assert s in project._repr_html_()
# Check __getitem__.
assert project[1] == w
assert len(project[:2]) == 2
l = [0, 1]
assert len(project[l]) == 2
assert len(project.get_mnemonics(['DT'])) == 4
html = project.curve_table_html()
assert "<table><tr><th>UWI</th><th>Data</th>" in html
assert "<th>DPHI_SAN</th>" in html
s = """<td style="background-color:#CCEECC; line-height:80%; padding:5px 4px 2px 4px;">DTS<div style="font-size:80%; float:right; padding:4px 0px 4px 6px; color:#CCCCCC;"></div><br /><span style="font-size:70%; color:#33AA33">us/ft</span></td>"""
assert s in html
def test_data_as_matrix():
alias = {'Sonic': ['DT', 'foo']}
project = Project.from_las('tests/*.las')
X_train, y_train = project.data_as_matrix(X_keys=['DEPT', 'HCAL', 'Sonic'],
y_key='CALI',
alias=alias,
window_length=1,
remove_zeros=True,
)
assert X_train.shape[0] == y_train.size
def test_data_as_matrix():
alias = {'Sonic': ['DT', 'foo']}
project = Project.from_las('tests/*.las')
X_train, y_train = project.data_as_matrix(
X_keys=['DEPT', 'HCAL', 'Sonic'],
y_key='CALI',
alias=alias,
window_length=1,
remove_zeros=True,
)
assert X_train.shape[0] == y_train.size
import streamlit as st
import json
import random
import pandas as pd
import plotly.graph_objects as go
from welly import Project
from pathlib import Path
import helper2
base_dir = "./data/McMurray_data"
fpath = Path(base_dir+"/las/*.LAS")
p = Project.from_las(str(fpath))
#get the first well. this need to be updated with the well list
df = p[0].df()
def app():
st.title('Correlation Panel')
st.write('well logs displayed below')
# first argument takes the titleof the selectionbox
# second argument takes options
f = open('/home/user/github_repo/t21-hack-SwellCorr/log_dict.json',)
log_inp = json.load(f)
def test_data_as_matrix():
alias = {'Sonic': ['DT', 'foo']}
project = Project.from_las('tests/*.las')
import json
import numpy as np
import pandas as pd
from pathlib import Path
import numpy as np
import helper
app = Dash(__name__)
# Create server variable with Flask server object for use with gunicorn
server = app.server
# # load well data
"""Need to add a method for the user to point to the directory or add additional las files later"""
#w = Well.from_las(str(Path("data/las/PoseidonNorth1Decim.LAS"))) #original example
p = Project.from_las(str(Path("data/McMurray_data/las/*.LAS")))
well_uwi = [w.uwi for w in p
] ##gets the well uwi data for use in the well-selector tool
df = p[0].df() ##gets data from the first well in the Welly Project
curve_list = df.columns.tolist(
) ##gets the column names for later use in the curve-selector tool
curve = curve_list[
0] ##gets the first curve name to be used as the first curve displayed in the plotly figure
## Load well top data
surface_picks_df = pd.read_table(Path('./data/McMurray_data/PICKS.TXT'),
usecols=['UWI', 'PICK', 'MD'])
#well dropdown selector
well_dropdown_options = [{
app = Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
# Create server variable with Flask server object for use with gunicorn
server = app.server
# Get las files
path = 'data/Poseidon_data/las/' # direct link to specific data
lasfiles = glob(path + '*.LAS')
# Get striplog files
path2 = 'data/Poseidon_data/tops/' # direct link to specific data
stripfiles = glob(path2 + '*.csv')
legend = Legend.from_csv(filename='data/Poseidon_data/tops_legend.csv'
) # direct link to specific data
p = Project.from_las(
'data/Poseidon_data/las/*.LAS') # direct link to specific data
well_uwi = [w.uwi for w in p
] ##gets the well uwi data for use in the well-selector tool
# Add striplogs to Project
# Striplog must have the same name as LAS file.
# e.g. Torosa-1.LAS and Torosa-1.csv
for w in p:
name = Path(w.fname).stem
strip = Striplog.from_csv(
f'data/Poseidon_data/tops/{name}.csv') # direct link to specific data
w.data['tops'] = strip
well = p[0] ##gets data from the first well in the Welly Project
curve_list = get_curves(
p) ##gets the column names for later use in the curve-selector tool
from welly import Project
from alaska import Alias, get_data_path
path = str(get_data_path("testcase1.las"))
# initialize aliaser
a = Alias()
# the parameters can also be customized as such:
# a = Alias(dictionary=True, keyword_extractor=True,
# model=True, prob_cutoff=.5)
# the parse function returns two dictionaries, one for parsed
# and another one for mnemonics not found using the aliaser
parsed, not_found = a.parse(path)
# print aliased mnemonics to screen
print("*" * 10, "Aliased dictionary", "*" * 10)
for i in parsed:
print("{}: {}".format(i, parsed[i]))
print("Not parsed with Aliaser:", not_found)
# feed parsed dictionary into welly, and leave the not aliased
# ones alone
p = Project.from_las(path)
data = p.df(keys=list(parsed.keys()), alias=parsed)
print(data)
# print the heatmap of the aliased mnemonics to visualize results
a.heatmap()
for fname in lasfiles:
print(' '*5, fname)
print('\n')
# Get striplog files
path2 = 'data/Poseidon_data/tops/'
print('\n STRIP PATH:', path2, '\n')
stripfiles = glob(path2 + '*.csv')
for fname in stripfiles:
print(' '*5, fname)
print('\n')
tops_legend = Legend.from_csv(filename='data/Poseidon_data/tops_legend.csv')
p = Project.from_las('data/Poseidon_data/las/*.LAS')
well_uwi = [w.uwi for w in p] ##gets the well uwi data for use in the well-selector tool
# Add striplogs to Project
# Striplog must have the same name as LAS file.
# e.g. Torosa-1.LAS and Torosa-1.csv
for w in p:
name = Path(w.fname).name.split('.')[0]
new_path = f'data/Poseidon_data/tops/{name}.csv'
print(name, new_path)
strip = Striplog.from_csv(f'data/Poseidon_data/tops/{name}.csv')
w.data['tops'] = strip
# Make the well correlation panel
def encode_xsection(p):
import json
import numpy as np
import pandas as pd
from pathlib import Path
import helper
app = Dash(__name__)
# Create server variable with Flask server object for use with gunicorn
server = app.server
# # load well data
"""Need to add a method for the user to point to the directory or add additional las files later"""
#w = Well.from_las(str(Path("well_picks/data/las/PoseidonNorth1Decim.LAS"))) #original example
p = Project.from_las(str(Path("well_picks/data/las/*.LAS")))
well_uwi = [w.uwi for w in p] ##gets the well uwi data for use in the well-selector tool
df = p[0].df() ##gets data from the first well in the Welly Project
curve_list = df.columns.tolist() ##gets the column names for later use in the curve-selector tool
curve = curve_list[0] ##gets the first curve name to be used as the first curve displayed in the plotly figure
## Load well top data
"""sample pick data, this will eventually need to load data from file or other source into the current dict"""
surface_picks = {"Sea Bed": 520.4, "Montara Formation": 4620, "Plover Formation (Top Volcanics)": 4703.2, "Plover Formation (Top Reservoir)": 4798.4, "Nome Formation": 5079}
#well dropdown selector
well_dropdown_options = [{'label': k, 'value': k} for k in well_uwi] ##list of wells to the dropdown
#tops dropdown options
from welly import Project
from alaska import Alias, get_data_path
PATH = str(get_data_path("722436A.las"))
# initialize aliaser
a = Alias()
# the parameters can also be customized as such:
# a = Alias(dictionary=True, keyword_extractor=True,
# model=True, prob_cutoff=.5)
# the parse function returns two dictionaries, one for parsed
# and another one for mnemonics not found using the aliaser
parsed, not_found = a.parse(PATH)
# print aliased mnemonics to screen
print("*" * 10, "Aliased dictionary", "*" * 10)
for i in parsed:
print("{}: {}".format(i, parsed[i]))
print("Not parsed with Aliaser:", not_found)
# feed parsed dictionary into welly, and leave the not aliased
# ones alone
p = Project.from_las(PATH)
data = p.df(keys=list(parsed.keys()), alias=parsed)
print(data)
# print the heatmap of the aliased mnemonics to visualize results
a.heatmap()
from welly import Well, Project
from glob import glob
# # load well data
"""Need to add a method for the user to point to the directory or add additional las files later"""
#w = Well.from_las(str(Path("well_picks/data/las/PoseidonNorth1Decim.LAS"))) #original example
# Get las files
path = 'las/'
print('\n LAS PATH:', path, '\n')
lasfiles = glob(path + '*.LAS')
for fname in lasfiles:
print(' ' * 5, fname)
print('\n')
# Get striplog files
path2 = 'tops/'
print('\n STRIP PATH:', path2, '\n')
stripfiles = glob(path2 + '*.csv')
for fname in stripfiles:
print(' ' * 5, fname)
print('\n')
p = Project.from_las("las/*.LAS")
well_uwi = [w.uwi for w in p
] ##gets the well uwi data for use in the well-selector tool
print(p)
