Skip to content

Snowflake Example ❄️

snowflake

Establishing a connection between an Snowflake database and whitson+ through our external API is a standard practice. While this example involves a Snowflake database, the majority of the steps are applicable to connecting any data source to whitson+. Read a Devon case study example here.

Auto Update Prod Data to whitson+: Workflow Overview

bhp input data model

Engineers spend 95% of their time uploading data. This example demonstrates an automated daily update of production data. The process adheres to a widely used structure: connecting to a database, verifying if the well is already uploaded to whitson+, and creating a new well with production data if it isn't. Alternatively, if the well exists, it appends the new production data to the existing entity. Let's explore the details!

Connect Snowflake to whitson+: Production Data Example

What does the snowflake_prod.py file do?

This code retrieves well and production data from Snowflake, then synchronizes or uploads that data to whitson+ domain (including creating or updating wells), and once all data is loaded, it runs BHP calculations for all wells within the specified project. The file uses a helper class WhitsonConnection in whitson_connect.py provided here.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
import whitson_connect
import pandas as pd

# ----------------------------------------------------------------------------------------------------------------
# 1. WHITSON CONNECTION
# ----------------------------------------------------------------------------------------------------------------

CLIENT = "your_domain_here" #This is the company suffix in your whitson urls ex. 'courses' in courses.whitson.com
CLIENT_ID = "your_client_id_here" # Available on request
CLIENT_SECRET = "your_client_secret" # Available on request

OVERWRITE_LAST_45_DAY_BOOL = True # Will overwrite last 45 days of prod data
SYNC_WELLHEADER_DATA = False

PROJECT_DICT = {
    ('Default'): 1,
}

PROJECT_ID_LIST = [value for value in PROJECT_DICT.values()]

whitson_connection = whitson_connect.WhitsonConnection(
    CLIENT, CLIENT_ID, CLIENT_SECRET
)

whitson_connection.access_token = whitson_connection.get_access_token_smart()

# ----------------------------------------------------------------------------------------------------------------
# 2. SNOWFLAKE CONNECTION
# ----------------------------------------------------------------------------------------------------------------

snowflake_connection = whitson_connection.snowflake_connection(
    account='YOUR_ACCOUNT',             # example: 'abc12345.east-us-1.azure'
    user='YOUR_USERNAME',               # example: 'WHITSON_READ'
    password='YOUR_PASSWORD',           # example: 'password123!'
    database='YOUR_DB_NAME'             # example: 'ABCDEFG_123456_WHITSON'
)

# ----------------------------------------------------------------------------------------------------------------
# 3. Wellheader Info
# ----------------------------------------------------------------------------------------------------------------

snowflake_query = """SELECT * FROM YOUR_DB_NAME.PUBLIC.WELL_DATA"""
snowflake_wells_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)
whitson_wells = whitson_connection.get_wells_from_projects(PROJECT_ID_LIST, 200)

for index, well in snowflake_wells_df.iterrows():
    wellname = well['well_name']
    if any(well["name"] == wellname for well in whitson_wells) and SYNC_WELLHEADER_DATA == False:
        print(f"Well with name '{wellname}' already exists.")
    else:
        well_info = {
            "project_id": PROJECT_DICT[('PERMIAN')],
            "name": well['well_name'],
            "uwi_api": well['uwi_api'],
            "t_res": well['t_res'] if well['t_res'] else 200,
            "p_res_i": well['p_res_i'] if well['p_res_i'] else 8000,
            "h": well['h'] if well['h'] else 200,
            "h_f": well['h_f'] if well['h_f'] else 200,
            "phi": well['phi'] if well['phi'] else 0.05,
            "l_w": float(well['l_w']) if well['l_w'] else 5280,
            "n_f": well['n_f'] if well['n_f'] else 100,
            "Sw_i": float(well['sw_i']) if well['sw_i'] else 30,
            "cr": well['cr'] if well['cr'] else 4,
            "gamma_m": well['gamma_m'] if well['gamma_m'] else 0,
            "gamma_f": well['gamma_f'] if well['gamma_f'] else 0,
            "salinity": well['salinity'] if well['salinity'] else 0,
            "country": well['country'],
            "state": well['state'],
            "county": well['county'],
            "sub_field": well['sub_field'],
            "reservoir": well['reservoir'],
            "formation": well['formation'],
            "surf_lat": well['surf_lat'],
            "surf_long": well['surf_long'],
            "bothole_lat": well['bothole_lat'],
            "bothole_long": well['bothole_long'],
            "operator": well['operator'],
            "pad_name": well['pad_name'],
            "reserve_classification": well['reserve_classification'],
            "fluid_pumped": float(well['fluid_pumped']) if pd.notna(well['fluid_pumped']) else None,  # Convert from gallons to STB * 0.0238095238
            "prop_pumped": float(well['prop_pumped']) if pd.notna(well['prop_pumped']) else None,
            "stages": int(well['stages']) if pd.notna(well['stages']) else None,
            "clusters": int(well['clusters']) if  pd.notna(well['clusters']) else None,
            "spacing": well['spacing'],
            "bounded": well['bounded'].lower() if well['bounded'] else 'bounded',
            "vintage": int(well['vintage']) if  pd.notna(well['vintage']) else None,
            "true_vertical_depth": float(well['true_vertical_depth']) if pd.notna(well['true_vertical_depth']) else None,
            "well_trajectory": well['well_trajectory'].lower() if well['well_trajectory'] else 'horizontal',
            "spud_date": well['spud_date'].strftime("%Y-%m-%d") if pd.notna(well['spud_date']) else None,
            "rig_release_date": well['rig_release_date'].strftime("%Y-%m-%d") if pd.notna(well['rig_release_date']) else None,
            "first_prod_date": well['first_prod_date'].strftime("%Y-%m-%d") if pd.notna(well['first_prod_date']) else None,
            "completion_date": well['completion_date'].strftime("%Y-%m-%d") if pd.notna(well['completion_date']) else None,
        }  
        if any(well["name"] == wellname for well in whitson_wells) and SYNC_WELLHEADER_DATA:
            print(f"Well with name {wellname} already exists, but we're updating the wellheader data.")
            well_id = whitson_connection.get_well_id_by_wellname(whitson_wells, wellname)
            well_info['id'] = well_id
            del well_info['project_id']
            del well_info['name']
            whitson_connection.edit_well_info(payload=[well_info])
            well_info = {}
        else:
            whitson_connection.create_well(payload=well_info)

# ----------------------------------------------------------------------------------------------------------------
# 4. Production Data
# ----------------------------------------------------------------------------------------------------------------

whitson_wells = whitson_connection.get_wells_from_projects(PROJECT_ID_LIST, 200)
uwi_id_dict = {item['uwi_api']: item['id'] for item in whitson_wells}

# Fetch daily production data from relevant Snowflake table
last_45_string = "where date >= DATEADD(DAY,-45, GETDATE())" if OVERWRITE_LAST_45_DAY_BOOL else ""
snowflake_query = f"""SELECT * FROM YOUR_DB_NAME.PUBLIC.PRODUCTION_DATA {last_45_string}"""
snowflake_prod_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)

# Bulk upload production data from Snowflake to whitson+
chunk_size = 25000 
num_chunks = len(snowflake_prod_df) // chunk_size + (1 if len(snowflake_prod_df) % chunk_size != 0 else 0)

for i in range(num_chunks):
    chunk_df = snowflake_prod_df[i * chunk_size: (i+1) * chunk_size]
    chunk_df.loc[:, 'well_id'] = chunk_df['well_id'].map(uwi_id_dict)
    payload = whitson_connection.convert_dataframe_to_prod_payload(chunk_df, columns_to_drop = ['insert_date'])
    whitson_connection.bulk_upload_production_to_well({"production_data": payload})

# ----------------------------------------------------------------------------------------------------------------
# 5. Run BHP calculations
# ----------------------------------------------------------------------------------------------------------------

whitson_connection.run_bhp_calc_in_projects(PROJECT_ID_LIST)

Connect Snowflake to whitson+: Bottomhole Pressure Example

What does the snowflake_bhp.py file do?

Retrieves well data (deviation survey, perforation, casing, tubing) from Snowflake, converts it into the appropriate payload, and uploads/synchronizes the well configuration to whitson+, including replacing the default wellbore configuration when needed. The code also checks whether the data has been uploaded previously, and if matching entries already exist, it will simply overwrite them. The file uses a helper class WhitsonConnection in whitson_connect.py provided here.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
import whitson_connect

CLIENT = "your_domain_here" # This is the company suffix in your whitson urls ex. 'courses' in courses.whitson.com
CLIENT_ID = "your_client_id_here" # Available on request
CLIENT_SECRET = "your_client_secret" # Available on request

PROJECT_DICT = {
    ('Default'): 1,
}

PROJECT_ID_LIST = [value for value in PROJECT_DICT.values()]

whitson_connection = whitson_connect.WhitsonConnection(
    CLIENT, CLIENT_ID, CLIENT_SECRET
)

whitson_connection.access_token = whitson_connection.get_access_token_smart()

# ------------------------------------------------------------------------------------------------------------------
# SNOWFLAKE CONNECTION
# ------------------------------------------------------------------------------------------------------------------

snowflake_connection = whitson_connection.snowflake_connection(
    account='YOUR_ACCOUNT',             # example: 'abc12345.east-us-1.azure'
    user='YOUR_USERNAME',               # example: 'WHITSON_READ'
    password='YOUR_PASSWORD',           # example: 'password123!'
    database='YOUR_DB_NAME'             # example: 'ABCDEFG_123456_WHITSON'
)

whitson_wells = whitson_connection.get_wells_from_projects(PROJECT_ID_LIST, 200)
uwi_id_dict = {item['uwi_api']: item['id'] for item in whitson_wells}

# ------------------------------------------------------------------------------------------------------------------
# 2.1 Upload well deviation surveys
# ------------------------------------------------------------------------------------------------------------------

snowflake_query = """SELECT * FROM YOUR_DB_NAME.PUBLIC.DEVIATION_SURVEY_DATA"""
snowflake_dev_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)

payloads_by_well = {}

for index, row in snowflake_dev_df.iterrows():
    uwi_api = row['well_id']
    md_value = row['md']
    tvd_value = row['tvd']

    if uwi_api in payloads_by_well:
        payloads_by_well[uwi_api].append({"md": md_value, "tvd": tvd_value})
    else:
        payloads_by_well[uwi_api] = [{"md": md_value, "tvd": tvd_value}]

for uwi_api, payload in payloads_by_well.items():
    well_id = uwi_id_dict.get(uwi_api)
    if whitson_connection.is_default_deviation_survey(well_id):
        try:
            whitson_connection.edit_well_deviation_survey(well_id=well_id, payload=payload)
        except:
            print(f'{uwi_api} (well_id: {well_id}): Something is off with this well id. This is the payload: {payload}')
            continue
    else:
            print(f'{uwi_api} (well_id: {well_id}): Well deviation survey already uploaded for this well.')

# ------------------------------------------------------------------------------------------------------------------
# 2.2 Upload top and bottom perforations
# ------------------------------------------------------------------------------------------------------------------

snowflake_query = """SELECT * FROM YOUR_DB_NAME.PUBLIC.PERFORATIONS"""
snowflake_perf_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)

processed_wells = {}

for index, row in snowflake_perf_df.iterrows():
    uwi_api = row['uwi']
    top_md = row['depthtop']
    bottom_md = row['depthbtm']

    if uwi_api in processed_wells:
        continue

    payload = {
        "top_perforation_md": top_md,
        "bottom_perforation_md": bottom_md
    }

    well_id = uwi_id_dict.get(uwi_api)

    if whitson_connection.is_default_perforated_interval(well_id):
        try: 
            whitson_connection.edit_perf_interval(well_id, payload=payload)
        except:
            print(f'{uwi_api} (well_id: {well_id}): Something is off with this well id. This is the payload: {payload}')
    else: 
        print(f'{uwi_api} (well_id: {well_id}): Perforated interval is already uploaded for this well.')

    processed_wells[uwi_api] = True

# -------------------------------------------------------------------------------------------------------------------
# 2.3.1 Upload Casings First
# -------------------------------------------------------------------------------------------------------------------

snowflake_query = """SELECT * FROM YOUR_DB_NAME.PUBLIC.CASING"""
snowflake_casing_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)
well_payloads = {}

def _get_well_casing_data(uwi, group):
    """ Returns the casing data in relevant format. Returns None if not a production casing is found. """

    if 'Production' not in group['casingdes'].values:
        return None, None

    well_id = uwi_id_dict.get(uwi)
    top_md = 0
    bottom_md = whitson_connection.get_max_md_well_deviation_data(well_id)
    d_casing_inner = whitson_connection.round_to_significant_digits(group['szidnommincalc'].min() * 39.37) # in this example DB is in m, need to convert to inches
    use_from_date = group['dttmspud'].iloc[0].strftime('%Y-%m-%d')

    well_casing_data = [ {
        "d_casing_inner": d_casing_inner,  
        "pipe_number": 1,
        "k_casing": roughness,
        "bottom_md": bottom_md,
        "top_md": top_md,  
    }
    ]

    return well_casing_data, use_from_date

# Define some example values
last_valve_open = True 
calculate_from_gauge = False 
compute_through = "flowing_side" 
compute_static_down_to = "end_of_tubing"
roughness = 0.0006 # default in whitson+
well_data_casing = []

for uwi, group in snowflake_casing_df.groupby('uwi'):

    well_data_casing, use_from_date = _get_well_casing_data(uwi, group)

    if well_data_casing is not None: 

        well_payload = {
            "use_from_date": use_from_date,
            "flow_path": "casing",  # Placeholder, replace with actual logic if available
            "lift_method": "none",  # Placeholder, replace with actual logic if available
            "gas_lift_config": 'automatic',  # Placeholder, replace with actual logic if available
            "last_valve_open": last_valve_open,
            "gauge_depth": None,  # Placeholder, replace with actual logic if available
            "calculate_from_gauge": calculate_from_gauge,
            "compute_through": compute_through,
            "compute_static_down_to": compute_static_down_to,
            "well_data_casing": well_data_casing,
            "well_data_tubing": [],  # Placeholder, add logic to populate if needed
            "gas_lift_data": []  # Placeholder, add logic to populate if needed
        }

        # Append the payload to the well_payloads dictionary
        if uwi not in well_payloads:
            well_payloads[uwi] = []

        well_payloads[uwi].append(well_payload)

# -------------------------------------------------------------------------------------------------------------------
# # 2.3.2 Upload Tubings Second
# -------------------------------------------------------------------------------------------------------------------

snowflake_query = """SELECT * FROM YOUR_DB_NAME.PUBLIC.TUBING"""
snowflake_tubing_df = whitson_connection.snowflake_table_to_dataframe(snowflake_connection, snowflake_query)

# Iterate through each UWI
for uwi, tubing_group in snowflake_tubing_df.groupby('uwi'):

    for install_date, tubing in tubing_group.groupby('dttmspud'):

        tubing = tubing[tubing['compsubtyp'] == 'tubing']
        tubing_bottom_md = tubing['depthbtm'].max() * 3.28084 # Convert from meter to ft
        install_date = install_date.strftime('%Y-%m-%d')

        # Filter rows where 'compsubtyp' is 'tubing'
        df_tubing = tubing[tubing['compsubtyp'] == 'tubing']

        # Check if all values in 'szidnom' and 'szodnom' are the same
        szidnom_unique = df_tubing['szidnom'].nunique()
        szodnom_unique = df_tubing['szodnom'].nunique()

        if szidnom_unique != 1 or szodnom_unique != 1:
            print("Values of 'szidnom' and/or 'szodnom' are not the same for all tubing sizes.")

        # Select the most common value for tubing ID and OD 'szidnom' and 'szodnom'
        tubing_id = whitson_connection.round_to_significant_digits(df_tubing['szidnom'].mode().iloc[0] * 39.37) # in this example DB is in m, need to convert to inches
        tubing_od = whitson_connection.round_to_significant_digits(df_tubing['szodnom'].mode().iloc[0] * 39.37) # in this example DB is in m, need to convert to inches

        if tubing_od <= tubing_id: 
            print(f'WARNING! Tubing ID ({tubing_od}) > Tubing OD ({tubing_id}). Tubing OD will be set to tubing ID / 0.84 : {tubing_od/0.84}')
            tubing_od = whitson_connection.round_to_significant_digits(tubing_id/0.84) 

        well_data_tubing = [
            {
                "pipe_number": 1,
                "d_tubing_inner": tubing_id, 
                "d_tubing_outer": tubing_od,
                "k_tubing": roughness,
                "bottom_md": tubing_bottom_md, # Assembly_Btm_Md of last tubing string
            }
        ]

        well_data_casing = well_payloads.get(uwi, [{}])[0].get('well_data_casing')

        if well_data_casing == None:
            continue 

        glv_exists = bool(tubing['des'].str.contains('AGL|GL', case=False, na=False).any())
        lift_method = 'gas_lift' if glv_exists else 'none'

        # Define the well payload for this api_no12
        well_payload = {
            "use_from_date": install_date,
            "flow_path": "unknown", 
            "lift_method": lift_method, 
            "gas_lift_config": 'automatic', 
            "last_valve_open": last_valve_open,
            "gauge_depth": None,  
            "calculate_from_gauge": calculate_from_gauge,
            "compute_through": compute_through,
            "compute_static_down_to": compute_static_down_to,
            "well_data_casing": well_data_casing,
            "well_data_tubing": well_data_tubing,
            "gas_lift_data": []  
        }

        # Append the payload to the well_payloads dictionary
        if uwi not in well_payloads:
            well_payloads[uwi] = []

        well_payloads[uwi].append(well_payload)


for uwi, new_well_configurations in well_payloads.items():
        well_id = uwi_id_dict.get(uwi)
        existing_wellbore_data = whitson_connection.get_well_data(well_id)

        # Delete the default wellbore if the well has a default
        try:
            if existing_wellbore_data and whitson_connection.is_default_well_configuration(existing_wellbore_data): 
                well_data_id = existing_wellbore_data[0]['id']
                whitson_connection.delete_wellbore_config_by_well_data_id(well_data_id=well_data_id)

            # Check if there is a well config upload for this date already
            for new_well_configuration in new_well_configurations:
                if whitson_connection.is_wellbore_configuration_already_uploaded(new_well_configuration, existing_wellbore_data):
                    print('already uploaded for this date')
                    continue
                else:
                    try:
                        whitson_connection.upload_well_data_to_well(well_id, new_well_configurations)
                    except:
                        print(str(uwi) +': failed for this well. Here is the payload. ' + str(new_well_configuration))
        except:
            print('Something went wrong. Here is the api number ' + str(well_id) + 'and existing wellbore data ' + str(existing_wellbore_data)

Connect Snowflake to whitson+: Analysis Shareback Example

What does the snowflake_analysis_shareback.py file do?

This script connects to Snowflake and whitson+ domain, retrieve well data and project scenarios along with their analysis summary results. The file uses a helper class WhitsonConnection in whitson_connect.py provided here.

   1
   2
   3
   4
   5
   6
   7
   8
   9
  10
  11
  12
  13
  14
  15
  16
  17
  18
  19
  20
  21
  22
  23
  24
  25
  26
  27
  28
  29
  30
  31
  32
  33
  34
  35
  36
  37
  38
  39
  40
  41
  42
  43
  44
  45
  46
  47
  48
  49
  50
  51
  52
  53
  54
  55
  56
  57
  58
  59
  60
  61
  62
  63
  64
  65
  66
  67
  68
  69
  70
  71
  72
  73
  74
  75
  76
  77
  78
  79
  80
  81
  82
  83
  84
  85
  86
  87
  88
  89
  90
  91
  92
  93
  94
  95
  96
  97
  98
  99
 100
 101
 102
 103
 104
 105
 106
 107
 108
 109
 110
 111
 112
 113
 114
 115
 116
 117
 118
 119
 120
 121
 122
 123
 124
 125
 126
 127
 128
 129
 130
 131
 132
 133
 134
 135
 136
 137
 138
 139
 140
 141
 142
 143
 144
 145
 146
 147
 148
 149
 150
 151
 152
 153
 154
 155
 156
 157
 158
 159
 160
 161
 162
 163
 164
 165
 166
 167
 168
 169
 170
 171
 172
 173
 174
 175
 176
 177
 178
 179
 180
 181
 182
 183
 184
 185
 186
 187
 188
 189
 190
 191
 192
 193
 194
 195
 196
 197
 198
 199
 200
 201
 202
 203
 204
 205
 206
 207
 208
 209
 210
 211
 212
 213
 214
 215
 216
 217
 218
 219
 220
 221
 222
 223
 224
 225
 226
 227
 228
 229
 230
 231
 232
 233
 234
 235
 236
 237
 238
 239
 240
 241
 242
 243
 244
 245
 246
 247
 248
 249
 250
 251
 252
 253
 254
 255
 256
 257
 258
 259
 260
 261
 262
 263
 264
 265
 266
 267
 268
 269
 270
 271
 272
 273
 274
 275
 276
 277
 278
 279
 280
 281
 282
 283
 284
 285
 286
 287
 288
 289
 290
 291
 292
 293
 294
 295
 296
 297
 298
 299
 300
 301
 302
 303
 304
 305
 306
 307
 308
 309
 310
 311
 312
 313
 314
 315
 316
 317
 318
 319
 320
 321
 322
 323
 324
 325
 326
 327
 328
 329
 330
 331
 332
 333
 334
 335
 336
 337
 338
 339
 340
 341
 342
 343
 344
 345
 346
 347
 348
 349
 350
 351
 352
 353
 354
 355
 356
 357
 358
 359
 360
 361
 362
 363
 364
 365
 366
 367
 368
 369
 370
 371
 372
 373
 374
 375
 376
 377
 378
 379
 380
 381
 382
 383
 384
 385
 386
 387
 388
 389
 390
 391
 392
 393
 394
 395
 396
 397
 398
 399
 400
 401
 402
 403
 404
 405
 406
 407
 408
 409
 410
 411
 412
 413
 414
 415
 416
 417
 418
 419
 420
 421
 422
 423
 424
 425
 426
 427
 428
 429
 430
 431
 432
 433
 434
 435
 436
 437
 438
 439
 440
 441
 442
 443
 444
 445
 446
 447
 448
 449
 450
 451
 452
 453
 454
 455
 456
 457
 458
 459
 460
 461
 462
 463
 464
 465
 466
 467
 468
 469
 470
 471
 472
 473
 474
 475
 476
 477
 478
 479
 480
 481
 482
 483
 484
 485
 486
 487
 488
 489
 490
 491
 492
 493
 494
 495
 496
 497
 498
 499
 500
 501
 502
 503
 504
 505
 506
 507
 508
 509
 510
 511
 512
 513
 514
 515
 516
 517
 518
 519
 520
 521
 522
 523
 524
 525
 526
 527
 528
 529
 530
 531
 532
 533
 534
 535
 536
 537
 538
 539
 540
 541
 542
 543
 544
 545
 546
 547
 548
 549
 550
 551
 552
 553
 554
 555
 556
 557
 558
 559
 560
 561
 562
 563
 564
 565
 566
 567
 568
 569
 570
 571
 572
 573
 574
 575
 576
 577
 578
 579
 580
 581
 582
 583
 584
 585
 586
 587
 588
 589
 590
 591
 592
 593
 594
 595
 596
 597
 598
 599
 600
 601
 602
 603
 604
 605
 606
 607
 608
 609
 610
 611
 612
 613
 614
 615
 616
 617
 618
 619
 620
 621
 622
 623
 624
 625
 626
 627
 628
 629
 630
 631
 632
 633
 634
 635
 636
 637
 638
 639
 640
 641
 642
 643
 644
 645
 646
 647
 648
 649
 650
 651
 652
 653
 654
 655
 656
 657
 658
 659
 660
 661
 662
 663
 664
 665
 666
 667
 668
 669
 670
 671
 672
 673
 674
 675
 676
 677
 678
 679
 680
 681
 682
 683
 684
 685
 686
 687
 688
 689
 690
 691
 692
 693
 694
 695
 696
 697
 698
 699
 700
 701
 702
 703
 704
 705
 706
 707
 708
 709
 710
 711
 712
 713
 714
 715
 716
 717
 718
 719
 720
 721
 722
 723
 724
 725
 726
 727
 728
 729
 730
 731
 732
 733
 734
 735
 736
 737
 738
 739
 740
 741
 742
 743
 744
 745
 746
 747
 748
 749
 750
 751
 752
 753
 754
 755
 756
 757
 758
 759
 760
 761
 762
 763
 764
 765
 766
 767
 768
 769
 770
 771
 772
 773
 774
 775
 776
 777
 778
 779
 780
 781
 782
 783
 784
 785
 786
 787
 788
 789
 790
 791
 792
 793
 794
 795
 796
 797
 798
 799
 800
 801
 802
 803
 804
 805
 806
 807
 808
 809
 810
 811
 812
 813
 814
 815
 816
 817
 818
 819
 820
 821
 822
 823
 824
 825
 826
 827
 828
 829
 830
 831
 832
 833
 834
 835
 836
 837
 838
 839
 840
 841
 842
 843
 844
 845
 846
 847
 848
 849
 850
 851
 852
 853
 854
 855
 856
 857
 858
 859
 860
 861
 862
 863
 864
 865
 866
 867
 868
 869
 870
 871
 872
 873
 874
 875
 876
 877
 878
 879
 880
 881
 882
 883
 884
 885
 886
 887
 888
 889
 890
 891
 892
 893
 894
 895
 896
 897
 898
 899
 900
 901
 902
 903
 904
 905
 906
 907
 908
 909
 910
 911
 912
 913
 914
 915
 916
 917
 918
 919
 920
 921
 922
 923
 924
 925
 926
 927
 928
 929
 930
 931
 932
 933
 934
 935
 936
 937
 938
 939
 940
 941
 942
 943
 944
 945
 946
 947
 948
 949
 950
 951
 952
 953
 954
 955
 956
 957
 958
 959
 960
 961
 962
 963
 964
 965
 966
 967
 968
 969
 970
 971
 972
 973
 974
 975
 976
 977
 978
 979
 980
 981
 982
 983
 984
 985
 986
 987
 988
 989
 990
 991
 992
 993
 994
 995
 996
 997
 998
 999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
import os
import sys

from dotenv import load_dotenv

project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
repo_root = os.path.abspath(os.path.join(project_root, "../.."))
sys.path.extend({project_root, repo_root})

if not load_dotenv(os.path.join(repo_root, ".env")):
    print(f"Warning: .env file not found at {repo_root}/.env")

import numpy as np
import pandas as pd
from aries_python_code import whitson_connect
import snowflake.connector
from snowflake.connector.pandas_tools import write_pandas
from tqdm import tqdm


def snowflake_analysis_shareback():
    # ----------------------------------------------------------------------------------------------------------------
    # 1. WHITSON CONNECTION
    # ----------------------------------------------------------------------------------------------------------------

    CLIENT = "your_domain_here"
    CLIENT_ID = "your_client_id_here"
    CLIENT_SECRET = "your_client_secret_here"

    PROJECT_DICT = {
        ("Default"): 1,
    }

    PROJECT_ID_LIST = [value for value in PROJECT_DICT.values()]

    whitson_connection = whitson_connect.WhitsonConnection(
        CLIENT, CLIENT_ID, CLIENT_SECRET
    )

    whitson_connection.access_token = whitson_connection.get_access_token_smart()

    whitson_wells = whitson_connection.get_wells_from_projects(PROJECT_ID_LIST)
    id_to_external_id_dict = {well["id"]: well["external_id"] for well in whitson_wells}

    # ----------------------------------------------------------------------------------------------------------------
    # 2. SNOWFLAKE CONNECTION
    # ----------------------------------------------------------------------------------------------------------------

    SCHEMA = "ENTER_YOUR_SCHEMA_HERE"
    RESULTS_TABLE_NAME = "ENTER_YOUR_TABLE_NAME_HERE"

    conn_params = {
        "account": "YOUR_ACCOUNT",
        "user": "YOUR_USERNAME",
        "private_key_file": "YOUR_PRIVATE_KEY_FILE",
        "private_key_file_pwd": "YOUR PRIVATE_KEY_FILE_PASSWORD",
        "warehouse": "YOUR_WAREHOUSE",
        "database": "YOUR_DATABASE",
        "schema": "YOUR_SCHEMA",
        "role": "YOUR_ROLE",
        "authenticator": "YOUR_AUTHENTICATOR",
    }

    conn = snowflake.connector.connect(**conn_params)

    # ----------------------------------------------------------------------------------------------------------------
    # 3. CREATE SNOWFLAKE TABLE TO SHARE IF NOT CREATED BEFORE
    # ----------------------------------------------------------------------------------------------------------------

    create_table_query = f"""
    CREATE TABLE IF NOT EXISTS {SCHEMA}.{RESULTS_TABLE_NAME} (
        WELL_ID INTEGER NOT NULL,
        EXTERNAL_ID VARCHAR(255),
        WELL_NAME VARCHAR(255) NOT NULL,
        UWI_API VARCHAR(255),
        PROJECT_ID NUMBER(38,0) NOT NULL,
        SCENARIO_NAME VARCHAR(255),
        DCA_EUR_O FLOAT,
        DCA_EUR_G FLOAT,
        DCA_EUR_W FLOAT,
        DCA_EUR_O_LW FLOAT,
        DCA_EUR_G_LW FLOAT,
        DCA_EUR_W_LW FLOAT,
        DCA_DATE_UPDATE DATE,
        DCA_UPDATE_BY VARCHAR(255),
        PNR_DCA_EUR_O FLOAT,
        PNR_DCA_EUR_G FLOAT,
        PNR_DCA_EUR_W FLOAT,
        PNR_DCA_EUR_O_LW FLOAT,
        PNR_DCA_EUR_G_LW FLOAT,
        PNR_DCA_EUR_W_LW FLOAT,
        PNR_DCA_DATE_UPDATE DATE,
        PNR_DCA_UPDATE_BY VARCHAR(255),
        BHP_DATE_UPDATE DATE,
        BHP_UPDATE_BY VARCHAR(255),
        BHP_FOR_CALC VARCHAR(255),
        IPR_INIT_PRESS FLOAT,
        IPR_PROD_INDEX_O FLOAT,
        IPR_PROD_INDEX_G FLOAT,
        MFMB_OOIP FLOAT,
        MFMB_OGIP FLOAT,
        MFMB_OWIP FLOAT,
        MFMB_VP FLOAT,
        MFMB_DATE_UPDATE DATE,
        MFMB_UPDATE_BY VARCHAR(255),
        RFA_EUR_O FLOAT,
        RFA_EUR_G FLOAT,
        RFA_EUR_W FLOAT,
        RFA_RF_O FLOAT,
        RFA_RF_W FLOAT,
        RFA_RF_G FLOAT,
        RFA_DATE_UPDATE DATE,
        RFA_UPDATE_BY VARCHAR(255),
        GMB_OOIP FLOAT,
        GMB_OGIP FLOAT,
        CLASSIC_RTA_TIME_FN VARCHAR(255),
        CLASSIC_RTA_PHASE VARCHAR(255),
        CLASSIC_RTA_LFP FLOAT,
        CLASSIC_RTA_OOIP FLOAT,
        CLASSIC_RTA_OGIP FLOAT,
        CLASSIC_RTA_K FLOAT,
        CLASSIC_RTA_XF FLOAT,
        CLASSIC_RTA_T_ELF FLOAT,
        CLASSIC_RTA_CT FLOAT,
        CLASSIC_RTA_FCD FLOAT,
        CLASSIC_RTA_SKIN FLOAT,
        CLASSIC_RTA_EUR FLOAT,
        CLASSIC_RTA_SLOPE FLOAT,
        CLASSIC_RTA_INTERCEPT FLOAT,
        CLASSIC_RTA_DATE_UPDATE DATE,
        CLASSIC_RTA_UPDATE_BY VARCHAR(255),
        FRACTION_RTA_TIME_FN VARCHAR(255),
        FRACTION_RTA_PHASE VARCHAR(255),
        FRACTION_RTA_LFP FLOAT,
        FRACTION_RTA_M FLOAT,
        FRACTION_RTA_DELTA FLOAT,
        FRACTION_RTA_B FLOAT AS (1 / NULLIF((1 - FRACTION_RTA_DELTA), 0)),
        FRACTION_RTA_CT FLOAT,
        FRACTION_RTA_DATE_UPDATE DATE,
        FRACTION_RTA_UPDATE_BY VARCHAR(255),
        NUMERIC_RTA_LFP FLOAT,
        NUMERIC_RTA_OOIP FLOAT,
        NUMERIC_RTA_OGIP FLOAT,
        NUMERIC_RTA_K FLOAT,
        NUMERIC_RTA_XF FLOAT,
        NUMERIC_RTA_DATE_UPDATE DATE,
        NUMERIC_RTA_UPDATE_BY VARCHAR(255),
        NUMERIC_MODEL_LFP FLOAT,
        NUMERIC_MODEL_OOIP FLOAT,
        NUMERIC_MODEL_OGIP FLOAT,
        NUMERIC_MODEL_OWIP FLOAT,
        NUMERIC_MODEL_K FLOAT,
        NUMERIC_MODEL_XF FLOAT,
        NUMERIC_MODEL_QO FLOAT,
        NUMERIC_MODEL_QG FLOAT,
        NUMERIC_MODEL_QW FLOAT,
        NUMERIC_MODEL_RF_O FLOAT,
        NUMERIC_MODEL_RF_G FLOAT,
        NUMERIC_MODEL_RF_W FLOAT,
        NUMERIC_MODEL_DATE_UPDATE DATE,
        NUMERIC_MODEL_UPDATE_BY VARCHAR(255),
        REL_PERM_SWC FLOAT,
        REL_PERM_SORW FLOAT,
        REL_PERM_SORG FLOAT,
        REL_PERM_SGC FLOAT,
        REL_PERM_NW FLOAT,
        REL_PERM_NOW FLOAT,
        REL_PERM_NG FLOAT,
        REL_PERM_NOG FLOAT,
        REL_PERM_KRWRO FLOAT,
        REL_PERM_KROCW FLOAT,
        REL_PERM_KRGRO FLOAT,
        SIMPLE_MB_RF_O FLOAT,
        SIMPLE_MB_RF_G FLOAT,
        PSAT FLOAT,
        PSAT_TYPE VARCHAR(255),
        TOTAL_OIL_FVF FLOAT,
        TOTAL_GOR FLOAT,
        RESERVOIR_CLASS VARCHAR(255),
        OIL_SAT FLOAT,
        OIL_FVF FLOAT,
        RS FLOAT,
        OIL_VISC FLOAT,
        OIL_DENSITY FLOAT,
        OIL_COMPRESSIBILITY FLOAT,
        GAS_SAT FLOAT,
        GAS_EXPANSION FLOAT,
        SOLUTION_CGR FLOAT,
        GAS_VISC FLOAT,
        GAS_DENSITY FLOAT,
        GAS_COMPRESSIBILITY FLOAT,
        SURF_OIL_SG FLOAT,
        SURF_GAS_SG FLOAT,
        SURF_LIQ_API FLOAT,
        OIL_PEAK_RATE FLOAT,
        OIL_PEAK_DAY FLOAT,
        OIL_CUM30 FLOAT,
        OIL_CUM60 FLOAT,
        OIL_CUM90 FLOAT,
        OIL_CUM180 FLOAT,
        OIL_CUM365 FLOAT,
        GAS_PEAK_RATE FLOAT,
        GAS_PEAK_DAY FLOAT,
        GAS_CUM30 FLOAT,
        GAS_CUM60 FLOAT,
        GAS_CUM90 FLOAT,
        GAS_CUM180 FLOAT,
        GAS_CUM365 FLOAT,
        WATER_PEAK_RATE FLOAT,
        WATER_PEAK_DAY FLOAT,
        WATER_CUM30 FLOAT,
        WATER_CUM60 FLOAT,
        WATER_CUM90 FLOAT,
        WATER_CUM180 FLOAT,
        WATER_CUM365 FLOAT,
        GOR_CUM30 FLOAT,
        GOR_CUM60 FLOAT,
        GOR_CUM90 FLOAT,
        GOR_CUM180 FLOAT,
        GOR_CUM365 FLOAT,
        OGR_CUM30 FLOAT,
        OGR_CUM60 FLOAT,
        OGR_CUM90 FLOAT,
        OGR_CUM180 FLOAT,
        OGR_CUM365 FLOAT,
        WOR_CUM30 FLOAT,
        WOR_CUM60 FLOAT,
        WOR_CUM90 FLOAT,
        WOR_CUM180 FLOAT,
        WOR_CUM365 FLOAT,
        WGR_CUM30 FLOAT,
        WGR_CUM60 FLOAT,
        WGR_CUM90 FLOAT,
        WGR_CUM180 FLOAT,
        WGR_CUM365 FLOAT,
        FIRST_PROD_DATE DATE,
        DAYS_ONLINE FLOAT,
        MONTHS_ONLINE FLOAT,
        YEARS_ONLINE FLOAT,
        OIL_IP30 FLOAT,
        OIL_IP60 FLOAT,
        OIL_IP90 FLOAT,
        OIL_IP180 FLOAT,
        OIL_IP365 FLOAT,
        GAS_IP30 FLOAT,
        GAS_IP60 FLOAT,
        GAS_IP90 FLOAT,
        GAS_IP180 FLOAT,
        GAS_IP365 FLOAT,
        WATER_IP30 FLOAT,
        WATER_IP60 FLOAT,
        WATER_IP90 FLOAT,
        WATER_IP180 FLOAT,
        WATER_IP365 FLOAT,
        QC_PVT VARCHAR(255),
        QC_DCA VARCHAR(255),
        QC_BHP VARCHAR(255),
        QC_FMB VARCHAR(255),
        QC_ANALYTICAL_RTA VARCHAR(255),
        QC_NUMERICAL_RTA VARCHAR(255),
        QC_NUMERICAL_MODEL VARCHAR(255),
        QC_IPR_VLP VARCHAR(255),
        QC_PNR_DCA VARCHAR(255),
        COMPUTER_RUN_DATE DATE
    );
    """

    conn.cursor().execute(create_table_query)

    # ---------------------------------------------------------------------------------------------------------------
    # 4. DROP AND CREATE SNOWFLAKE STG TABLE IF NOT CREATED BEFORE.
    # ---------------------------------------------------------------------------------------------------------------

    staging_table_query = f"CREATE OR REPLACE TEMP TABLE {SCHEMA}.{RESULTS_TABLE_NAME}_STG LIKE {SCHEMA}.{RESULTS_TABLE_NAME}"
    conn.cursor().execute(staging_table_query)

    # ---------------------------------------------------------------------------------------------------------------
    # 5. FETCH RESULTS SUMMARY DATA & SAVE TO RELEVANT TABLE
    # ---------------------------------------------------------------------------------------------------------------

    def flatten_entry(entry, project_id):

        wd = entry.get("Well Data", {})
        dca = entry.get("Decline Curve Analysis", {})
        pnr = entry.get("PNR DCA", {})
        bhp = entry.get("BHP", {})
        pri = entry.get("pRi from IPR", {})
        mfmb = entry.get("Multiphase Flowing Material Balance", {})
        rfa = entry.get("Recovery Factor Analysis", {})
        gmb = entry.get("Gas Material Balance", {})
        crta = entry.get("Classical RTA", {})
        frta = entry.get("Fractional RTA", {})
        nrta = entry.get("Numerical RTA", {})
        nmodel = entry.get("Numerical Model", {})
        kr = entry.get("Relative Permeability", {})
        smbal = entry.get("Simple Mat Bal", {})
        fluid = entry.get("Fluid Data at Initial Reservoir Conditions", {})
        surf = entry.get("Surface Gravities", {})
        prod = entry.get("Production Attributes", {})
        qc = entry.get("Quality Checks", {})

        return {
            "WELL_ID": entry.get("well_id", None),
            "EXTERNAL_ID": wd.get("External ID", None),
            "WELL_NAME": wd.get("Well Name"),
            "UWI_API": wd.get("UWI/API", None),
            "PROJECT_ID": project_id,
            "SCENARIO_NAME": wd.get("Scenario"),
            "DCA_EUR_O": dca.get("EURo (MSTB)", None),
            "DCA_EUR_G": dca.get("EURg (MMscf)", None),
            "DCA_EUR_W": dca.get("EURw (MSTB)", None),
            "DCA_EUR_O_LW": dca.get("EURo per Lw (STB/ft)", None),
            "DCA_EUR_G_LW": dca.get("EURg per Lw (Mscf/ft)", None),
            "DCA_EUR_W_LW": dca.get("EURw per Lw (STB/ft)", None),
            "DCA_DATE_UPDATE": dca.get("Date Updated", None),
            "DCA_UPDATE_BY": dca.get("Updated By", None),
            "PNR_DCA_EUR_O": pnr.get("EURo (MSTB)", None),
            "PNR_DCA_EUR_G": pnr.get("EURg (MMscf)", None),
            "PNR_DCA_EUR_W": pnr.get("EURw (MSTB)", None),
            "PNR_DCA_EUR_O_LW": pnr.get("EURo per Lw (STB/ft)", None),
            "PNR_DCA_EUR_G_LW": pnr.get("EURg per Lw (Mscf/ft)", None),
            "PNR_DCA_EUR_W_LW": pnr.get("EURw per Lw (STB/ft)", None),
            "PNR_DCA_DATE_UPDATE": pnr.get("Date Updated", None),
            "PNR_DCA_UPDATE_BY": pnr.get("Updated By", None),
            "BHP_DATE_UPDATE": bhp.get("Date Updated", None),
            "BHP_UPDATE_BY": bhp.get("Updated By", None),
            "BHP_FOR_CALC": bhp.get("BHP Used For Calculations", None),
            "IPR_INIT_PRESS": pri.get("Initial Reservoir Pressure (psia)", None),
            "IPR_PROD_INDEX_O": pri.get(
                "Productivity Index Oil ((STB/day)/psia)", None
            ),
            "IPR_PROD_INDEX_G": pri.get(
                "Productivity Index Gas (Mscf/day)/(10^6*psia^2/cp))", None
            ),
            "MFMB_OOIP": mfmb.get("OOIP (MSTB)", None),
            "MFMB_OGIP": mfmb.get("OGIP (MMscf)", None),
            "MFMB_OWIP": mfmb.get("OWIP (MSTB)", None),
            "MFMB_VP": mfmb.get("Vp (MRB)", None),
            "MFMB_DATE_UPDATE": mfmb.get("Date Updated", None),
            "MFMB_UPDATE_BY": mfmb.get("Updated By", None),
            "RFA_EUR_O": rfa.get("Oil EUR (MSTB)", None),
            "RFA_EUR_G": rfa.get("Gas EUR (MMscf)", None),
            "RFA_EUR_W": rfa.get("Water EUR (MSTB)", None),
            "RFA_RF_O": rfa.get("Oil RF (%)", None),
            "RFA_RF_W": rfa.get("Water RF (%)", None),
            "RFA_RF_G": rfa.get("Gas RF (%)", None),
            "RFA_DATE_UPDATE": rfa.get("Date Updated", None),
            "RFA_UPDATE_BY": rfa.get("Updated By", None),
            "GMB_OOIP": gmb.get("OOIP (MSTB)", None),
            "GMB_OGIP": gmb.get("OGIP (MMscf)", None),
            "CLASSIC_RTA_TIME_FN": crta.get("Time Function", None),
            "CLASSIC_RTA_PHASE": crta.get("Phase", None),
            "CLASSIC_RTA_LFP": crta.get("LFP (ft2/md1/2)", None),
            "CLASSIC_RTA_OOIP": crta.get("OOIP (MSTB)", None),
            "CLASSIC_RTA_OGIP": crta.get("OGIP (MMscf)", None),
            "CLASSIC_RTA_K": crta.get("k (nd)", None),
            "CLASSIC_RTA_XF": crta.get("xf (ft)", None),
            "CLASSIC_RTA_T_ELF": crta.get("t_elf", None),
            "CLASSIC_RTA_CT": crta.get("cT (e-6/psia)", None),
            "CLASSIC_RTA_FCD": (
                crta.get("Fcd", None)
                if (crta.get("Fcd", None) not in ["-", "Infinity"])
                else float("inf")
            ),  # Need to handle '-' & 'Infinity
            "CLASSIC_RTA_SKIN": crta.get("Skin", None),
            "CLASSIC_RTA_EUR": crta.get("EUR (MSTB/MMscf)", None),
            "CLASSIC_RTA_SLOPE": crta.get("Slope", None),
            "CLASSIC_RTA_INTERCEPT": crta.get("Intercept", None),
            "CLASSIC_RTA_DATE_UPDATE": crta.get("Date Updated", None),
            "CLASSIC_RTA_UPDATE_BY": crta.get("Updated By", None),
            "FRACTION_RTA_TIME_FN": frta.get("Time Function", None),
            "FRACTION_RTA_PHASE": frta.get("Phase", None),
            "FRACTION_RTA_LFP": frta.get("LFP (ft2/md1/2)", None),
            "FRACTION_RTA_M": frta.get("m", None),
            "FRACTION_RTA_DELTA": frta.get("delta", None),
            "FRACTION_RTA_CT": frta.get("cT (e-6/psia)", None),
            "FRACTION_RTA_DATE_UPDATE": frta.get("Date Updated", None),
            "FRACTION_RTA_UPDATE_BY": frta.get("Updated By", None),
            "NUMERIC_RTA_LFP": nrta.get("LFP (ft2/md1/2)", None),
            "NUMERIC_RTA_OOIP": nrta.get("OOIP (MSTB)", None),
            "NUMERIC_RTA_OGIP": nrta.get("OGIP (MMscf)", None),
            "NUMERIC_RTA_K": nrta.get("k (nd)", None),
            "NUMERIC_RTA_XF": nrta.get("xf (ft)", None),
            "NUMERIC_RTA_DATE_UPDATE": nrta.get("Date Updated", None),
            "NUMERIC_RTA_UPDATE_BY": nrta.get("Updated By", None),
            "NUMERIC_MODEL_LFP": nmodel.get("LFP (ft2/md1/2)", None),
            "NUMERIC_MODEL_OOIP": nmodel.get("OOIP (MSTB)", None),
            "NUMERIC_MODEL_OGIP": nmodel.get("OGIP (MMscf)", None),
            "NUMERIC_MODEL_OWIP": nmodel.get("OWIP (MSTB)", None),
            "NUMERIC_MODEL_K": nmodel.get("k (nd)", None),
            "NUMERIC_MODEL_XF": nmodel.get("xf (ft)", None),
            "NUMERIC_MODEL_QO": nmodel.get("Qo (MSTB)", None),
            "NUMERIC_MODEL_QG": nmodel.get("Qg (MMscf)", None),
            "NUMERIC_MODEL_QW": nmodel.get("Qw (MSTB)", None),
            "NUMERIC_MODEL_RF_O": nmodel.get("Oil RF (%)", None),
            "NUMERIC_MODEL_RF_G": nmodel.get("Gas RF (%)", None),
            "NUMERIC_MODEL_RF_W": nmodel.get("Water RF (%)", None),
            "NUMERIC_MODEL_DATE_UPDATE": nmodel.get("Date Updated", None),
            "NUMERIC_MODEL_UPDATE_BY": nmodel.get("Updated By", None),
            "REL_PERM_SWC": kr.get("Swc", None),
            "REL_PERM_SORW": kr.get("Sorw", None),
            "REL_PERM_SORG": kr.get("Sorg", None),
            "REL_PERM_SGC": kr.get("Sgc", None),
            "REL_PERM_NW": kr.get("nw", None),
            "REL_PERM_NOW": kr.get("now", None),
            "REL_PERM_NG": kr.get("ng", None),
            "REL_PERM_NOG": kr.get("nog", None),
            "REL_PERM_KRWRO": kr.get("krwro", None),
            "REL_PERM_KROCW": kr.get("krocw", None),
            "REL_PERM_KRGRO": kr.get("krgro", None),
            "SIMPLE_MB_RF_O": smbal.get("Oil RF (%)", None),
            "SIMPLE_MB_RF_G": smbal.get("Gas RF (%)", None),
            "PSAT": fluid.get("Psat (psia)", None),
            "PSAT_TYPE": fluid.get("Psat type", None),
            "TOTAL_OIL_FVF": fluid.get("Total Oil FVF (RB/STB)", None),
            "TOTAL_GOR": fluid.get("Total GOR (scf/STB)", None),
            "RESERVOIR_CLASS": fluid.get("Reservoir Classification", None),
            "OIL_SAT": fluid.get("Oil Saturation (%)", None),
            "OIL_FVF": fluid.get("Oil FVF - Bo (RB/STB)", None),
            "RS": fluid.get("Solution GOR - Rs (scf/STB)", None),
            "OIL_VISC": fluid.get("Oil viscosity - μo (cp)", None),
            "OIL_DENSITY": fluid.get("Reservoir Oil Density - ρo (lbm/ft3)", None),
            "OIL_COMPRESSIBILITY": fluid.get(
                "Oil compressibility - co (e-6/psia)", None
            ),
            "GAS_SAT": fluid.get("Gas Saturation (%)", None),
            "GAS_EXPANSION": fluid.get("Gas Expansion - bgd (scf/RB)", None),
            "SOLUTION_CGR": fluid.get("Solution CGR - rs - Rv (STB/MMscf)", None),
            "GAS_VISC": fluid.get("Gas viscosity - μg (cp)", None),
            "GAS_DENSITY": fluid.get("Reservoir Gas Density - ρg (lbm/ft3)", None),
            "GAS_COMPRESSIBILITY": fluid.get(
                "Gas compressibility - cg (e-6/psia)", None
            ),
            "SURF_OIL_SG": surf.get("Oil Specific Gravity", None),
            "SURF_GAS_SG": surf.get("Gas Specific Gravity", None),
            "SURF_LIQ_API": surf.get("Liquid API Gravity", None),
            "OIL_PEAK_RATE": prod.get("Oil Peak Rate (STB/d)", None),
            "OIL_PEAK_DAY": prod.get("Oil Peak Day (d)", None),
            "OIL_CUM30": prod.get("Oil CUM30 (MSTB)", None),
            "OIL_CUM60": prod.get("Oil CUM60 (MSTB)", None),
            "OIL_CUM90": prod.get("Oil CUM90 (MSTB)", None),
            "OIL_CUM180": prod.get("Oil CUM180 (MSTB)", None),
            "OIL_CUM365": prod.get("Oil CUM365 (MSTB)", None),
            "GAS_PEAK_RATE": prod.get("Gas Peak Rate (MMscf/d)", None),
            "GAS_PEAK_DAY": prod.get("Gas Peak Day (d)", None),
            "GAS_CUM30": prod.get("Gas CUM30 (MMscf)", None),
            "GAS_CUM60": prod.get("Gas CUM60 (MMscf)", None),
            "GAS_CUM90": prod.get("Gas CUM90 (MMscf)", None),
            "GAS_CUM180": prod.get("Gas CUM180 (MMscf)", None),
            "GAS_CUM365": prod.get("Gas CUM365 (MMscf)", None),
            "WATER_PEAK_RATE": prod.get("Water Peak Rate (STB/d)", None),
            "WATER_PEAK_DAY": prod.get("Water Peak Day (d)", None),
            "WATER_CUM30": prod.get("Water CUM30 (MSTB)", None),
            "WATER_CUM60": prod.get("Water CUM60 (MSTB)", None),
            "WATER_CUM90": prod.get("Water CUM90 (MSTB)", None),
            "WATER_CUM180": prod.get("Water CUM180 (MSTB)", None),
            "WATER_CUM365": prod.get("Water CUM365 (MSTB)", None),
            "GOR_CUM30": prod.get("GOR CUM30 (scf/STB)", None),
            "GOR_CUM60": prod.get("GOR CUM60 (scf/STB)", None),
            "GOR_CUM90": prod.get("GOR CUM90 (scf/STB)", None),
            "GOR_CUM180": prod.get("GOR CUM180 (scf/STB)", None),
            "GOR_CUM365": prod.get("GOR CUM365 (scf/STB)", None),
            "OGR_CUM30": prod.get("OGR CUM30 (STB/MMscf)", None),
            "OGR_CUM60": prod.get("OGR CUM60 (STB/MMscf)", None),
            "OGR_CUM90": prod.get("OGR CUM90 (STB/MMscf)", None),
            "OGR_CUM180": prod.get("OGR CUM180 (STB/MMscf)", None),
            "OGR_CUM365": prod.get("OGR CUM365 (STB/MMscf)", None),
            "WOR_CUM30": prod.get("WOR CUM30 (STB/STB)", None),
            "WOR_CUM60": prod.get("WOR CUM60 (STB/STB)", None),
            "WOR_CUM90": prod.get("WOR CUM90 (STB/STB)", None),
            "WOR_CUM180": prod.get("WOR CUM180 (STB/STB)", None),
            "WOR_CUM365": prod.get("WOR CUM365 (STB/STB)", None),
            "WGR_CUM30": prod.get("WGR CUM30 (STB/MMscf)", None),
            "WGR_CUM60": prod.get("WGR CUM60 (STB/MMscf)", None),
            "WGR_CUM90": prod.get("WGR CUM90 (STB/MMscf)", None),
            "WGR_CUM180": prod.get("WGR CUM180 (STB/MMscf)", None),
            "WGR_CUM365": prod.get("WGR CUM365 (STB/MMscf)", None),
            "FIRST_PROD_DATE": prod.get("First Prod Date", None),
            "DAYS_ONLINE": prod.get("Days Online (d)", None),
            "MONTHS_ONLINE": prod.get("Months Online (m)", None),
            "YEARS_ONLINE": prod.get("Years Online (y)", None),
            "OIL_IP30": prod.get("Oil IP30 (STB/d)", None),
            "OIL_IP60": prod.get("Oil IP60 (STB/d)", None),
            "OIL_IP90": prod.get("Oil IP90 (STB/d)", None),
            "OIL_IP180": prod.get("Oil IP180 (STB/d)", None),
            "OIL_IP365": prod.get("Oil IP365 (STB/d)", None),
            "GAS_IP30": prod.get("Gas IP30 (MMscf/d)", None),
            "GAS_IP60": prod.get("Gas IP60 (MMscf/d)", None),
            "GAS_IP90": prod.get("Gas IP90 (MMscf/d)", None),
            "GAS_IP180": prod.get("Gas IP180 (MMscf/d)", None),
            "GAS_IP365": prod.get("Gas IP365 (MMscf/d)", None),
            "WATER_IP30": prod.get("Water IP30 (STB/d)", None),
            "WATER_IP60": prod.get("Water IP60 (STB/d)", None),
            "WATER_IP90": prod.get("Water IP90 (STB/d)", None),
            "WATER_IP180": prod.get("Water IP180 (STB/d)", None),
            "WATER_IP365": prod.get("Water IP365 (STB/d)", None),
            "QC_PVT": qc.get("PVT", None),
            "QC_DCA": qc.get("DCA", None),
            "QC_BHP": qc.get("BHP", None),
            "QC_FMB": qc.get("FMB", None),
            "QC_ANALYTICAL_RTA": qc.get("Analytical RTA", None),
            "QC_NUMERICAL_RTA": qc.get("Numerical RTA", None),
            "QC_NUMERICAL_MODEL": qc.get("Numerical Model", None),
            "QC_IPR_VLP": qc.get("IPR/VLP", None),
            "QC_PNR_DCA": qc.get("PNR DCA", None),
        }

    for project_id in PROJECT_ID_LIST:
        result_dfs = []
        whitson_wells = whitson_connection.get_wells_and_scenarios_from_projects(
            [project_id], 3000
        )
        id_to_external_id_dict = {
            well["id"]: well["external_id"] for well in whitson_wells[0]
        }
        main_ids = [well["id"] for well in whitson_wells[0]]
        scenario_ids = [well["id"] for well in whitson_wells[1]]
        scenario_id_to_external_id_dict = {
            well["id"]: id_to_external_id_dict.get(well["main_well_id"])
            for well in whitson_wells[1]
        }
        id_to_external_id_dict = (
            id_to_external_id_dict | scenario_id_to_external_id_dict
        )

        well_ids = main_ids + scenario_ids

        chunk_size = 1500
        for i in range(0, len(well_ids), chunk_size):
            flat_data = []
            results = whitson_connection.get_mass_well_custom_results(
                well_ids[i : i + chunk_size]
            )
            print(i)
            for entry in results["data"]:
                temp = flatten_entry(entry, project_id)
                flat_data.append(temp)

            result_dfs.append(pd.DataFrame(flat_data))

        result_dfs = pd.concat(result_dfs, ignore_index=True)

        result_dfs = result_dfs.replace("no data", None)
        result_dfs["EXTERNAL_ID"] = result_dfs["WELL_ID"].map(id_to_external_id_dict)
        result_dfs.dropna(subset=["EXTERNAL_ID", "WELL_NAME"], inplace=True)
        result_dfs.drop_duplicates(
            subset=["EXTERNAL_ID", "PROJECT_ID", "SCENARIO_NAME"], inplace=True
        )
        result_dfs["COMPUTER_RUN_DATE"] = pd.Timestamp.today().date()
        print(
            f"Dataframe holds {result_dfs.memory_usage(deep=True).sum()/ (1024 ** 2)} MB with data. "
        )

        write_pandas(conn, result_dfs, f"{RESULTS_TABLE_NAME}_STG")

    # ---------------------------------------------------------------------------------------------------------------
    # 6. FETCH AND LOAD DATA FROM STAGING TABLE
    # ---------------------------------------------------------------------------------------------------------------

    merge_query = f"""
        MERGE INTO {SCHEMA}.{RESULTS_TABLE_NAME} AS target
        USING {SCHEMA}.{RESULTS_TABLE_NAME}_STG AS source
        ON target.WELL_ID = source.WELL_ID
        AND target.PROJECT_ID = source.PROJECT_ID
        AND target.SCENARIO_NAME = source.SCENARIO_NAME
        WHEN MATCHED THEN
            UPDATE SET
                target.WELL_ID = source.WELL_ID,
                target.EXTERNAL_ID = source.EXTERNAL_ID,
                target.WELL_NAME = source.WELL_NAME,
                target.UWI_API = source.UWI_API,
                target.PROJECT_ID = source.PROJECT_ID,
                target.SCENARIO_NAME = source.SCENARIO_NAME,
                target.DCA_EUR_O = source.DCA_EUR_O,
                target.DCA_EUR_G = source.DCA_EUR_G,
                target.DCA_EUR_W = source.DCA_EUR_W,
                target.DCA_EUR_O_LW = source.DCA_EUR_O_LW,
                target.DCA_EUR_G_LW = source.DCA_EUR_G_LW,
                target.DCA_EUR_W_LW = source.DCA_EUR_W_LW,
                target.DCA_DATE_UPDATE = source.DCA_DATE_UPDATE,
                target.DCA_UPDATE_BY = source.DCA_UPDATE_BY,

                target.PNR_DCA_EUR_O = source.PNR_DCA_EUR_O,
                target.PNR_DCA_EUR_G = source.PNR_DCA_EUR_G,
                target.PNR_DCA_EUR_W = source.PNR_DCA_EUR_W,
                target.PNR_DCA_EUR_O_LW = source.PNR_DCA_EUR_O_LW,
                target.PNR_DCA_EUR_G_LW = source.PNR_DCA_EUR_G_LW,
                target.PNR_DCA_EUR_W_LW = source.PNR_DCA_EUR_W_LW,
                target.PNR_DCA_DATE_UPDATE = source.PNR_DCA_DATE_UPDATE,
                target.PNR_DCA_UPDATE_BY = source.PNR_DCA_UPDATE_BY,

                target.BHP_DATE_UPDATE = source.BHP_DATE_UPDATE,
                target.BHP_UPDATE_BY = source.BHP_UPDATE_BY,
                target.BHP_FOR_CALC = source.BHP_FOR_CALC,

                target.IPR_INIT_PRESS = source.IPR_INIT_PRESS,
                target.IPR_PROD_INDEX_O = source.IPR_PROD_INDEX_O,
                target.IPR_PROD_INDEX_G = source.IPR_PROD_INDEX_G,

                target.MFMB_OOIP = source.MFMB_OOIP,
                target.MFMB_OGIP = source.MFMB_OGIP,
                target.MFMB_OWIP = source.MFMB_OWIP,
                target.MFMB_VP = source.MFMB_VP,
                target.MFMB_DATE_UPDATE = source.MFMB_DATE_UPDATE,
                target.MFMB_UPDATE_BY = source.MFMB_UPDATE_BY,

                target.RFA_EUR_O = source.RFA_EUR_O,
                target.RFA_EUR_G = source.RFA_EUR_G,
                target.RFA_EUR_W = source.RFA_EUR_W,
                target.RFA_RF_O = source.RFA_RF_O,
                target.RFA_RF_W = source.RFA_RF_W,
                target.RFA_RF_G = source.RFA_RF_G,
                target.RFA_DATE_UPDATE = source.RFA_DATE_UPDATE,
                target.RFA_UPDATE_BY = source.RFA_UPDATE_BY,

                target.GMB_OOIP = source.GMB_OOIP,
                target.GMB_OGIP = source.GMB_OGIP,

                target.CLASSIC_RTA_TIME_FN = source.CLASSIC_RTA_TIME_FN,
                target.CLASSIC_RTA_PHASE = source.CLASSIC_RTA_PHASE,
                target.CLASSIC_RTA_LFP = source.CLASSIC_RTA_LFP,
                target.CLASSIC_RTA_OOIP = source.CLASSIC_RTA_OOIP,
                target.CLASSIC_RTA_OGIP = source.CLASSIC_RTA_OGIP,
                target.CLASSIC_RTA_K = source.CLASSIC_RTA_K,
                target.CLASSIC_RTA_XF = source.CLASSIC_RTA_XF,
                target.CLASSIC_RTA_T_ELF = source.CLASSIC_RTA_T_ELF,
                target.CLASSIC_RTA_CT = source.CLASSIC_RTA_CT,
                target.CLASSIC_RTA_FCD = source.CLASSIC_RTA_FCD,
                target.CLASSIC_RTA_SKIN = source.CLASSIC_RTA_SKIN,
                target.CLASSIC_RTA_EUR = source.CLASSIC_RTA_EUR,
                target.CLASSIC_RTA_SLOPE = source.CLASSIC_RTA_SLOPE,
                target.CLASSIC_RTA_INTERCEPT = source.CLASSIC_RTA_INTERCEPT,
                target.CLASSIC_RTA_DATE_UPDATE = source.CLASSIC_RTA_DATE_UPDATE,
                target.CLASSIC_RTA_UPDATE_BY = source.CLASSIC_RTA_UPDATE_BY,

                target.FRACTION_RTA_TIME_FN = source.FRACTION_RTA_TIME_FN,
                target.FRACTION_RTA_PHASE = source.FRACTION_RTA_PHASE,
                target.FRACTION_RTA_LFP = source.FRACTION_RTA_LFP,
                target.FRACTION_RTA_M = source.FRACTION_RTA_M,
                target.FRACTION_RTA_DELTA = source.FRACTION_RTA_DELTA,
                target.FRACTION_RTA_CT = source.FRACTION_RTA_CT,
                target.FRACTION_RTA_DATE_UPDATE = source.FRACTION_RTA_DATE_UPDATE,
                target.FRACTION_RTA_UPDATE_BY = source.FRACTION_RTA_UPDATE_BY,

                target.NUMERIC_RTA_LFP = source.NUMERIC_RTA_LFP,
                target.NUMERIC_RTA_OOIP = source.NUMERIC_RTA_OOIP,
                target.NUMERIC_RTA_OGIP = source.NUMERIC_RTA_OGIP,
                target.NUMERIC_RTA_K = source.NUMERIC_RTA_K,
                target.NUMERIC_RTA_XF = source.NUMERIC_RTA_XF,
                target.NUMERIC_RTA_DATE_UPDATE = source.NUMERIC_RTA_DATE_UPDATE,
                target.NUMERIC_RTA_UPDATE_BY = source.NUMERIC_RTA_UPDATE_BY,

                target.NUMERIC_MODEL_LFP = source.NUMERIC_MODEL_LFP,
                target.NUMERIC_MODEL_OOIP = source.NUMERIC_MODEL_OOIP,
                target.NUMERIC_MODEL_OGIP = source.NUMERIC_MODEL_OGIP,
                target.NUMERIC_MODEL_OWIP = source.NUMERIC_MODEL_OWIP,
                target.NUMERIC_MODEL_K = source.NUMERIC_MODEL_K,
                target.NUMERIC_MODEL_XF = source.NUMERIC_MODEL_XF,
                target.NUMERIC_MODEL_QO = source.NUMERIC_MODEL_QO,
                target.NUMERIC_MODEL_QG = source.NUMERIC_MODEL_QG,
                target.NUMERIC_MODEL_QW = source.NUMERIC_MODEL_QW,
                target.NUMERIC_MODEL_RF_O = source.NUMERIC_MODEL_RF_O,
                target.NUMERIC_MODEL_RF_G = source.NUMERIC_MODEL_RF_G,
                target.NUMERIC_MODEL_RF_W = source.NUMERIC_MODEL_RF_W,
                target.NUMERIC_MODEL_DATE_UPDATE = source.NUMERIC_MODEL_DATE_UPDATE,
                target.NUMERIC_MODEL_UPDATE_BY = source.NUMERIC_MODEL_UPDATE_BY,

                target.REL_PERM_SWC = source.REL_PERM_SWC,
                target.REL_PERM_SORW = source.REL_PERM_SORW,
                target.REL_PERM_SORG = source.REL_PERM_SORG,
                target.REL_PERM_SGC = source.REL_PERM_SGC,
                target.REL_PERM_NW = source.REL_PERM_NW,
                target.REL_PERM_NOW = source.REL_PERM_NOW,
                target.REL_PERM_NG = source.REL_PERM_NG,
                target.REL_PERM_NOG = source.REL_PERM_NOG,
                target.REL_PERM_KRWRO = source.REL_PERM_KRWRO,
                target.REL_PERM_KROCW = source.REL_PERM_KROCW,
                target.REL_PERM_KRGRO = source.REL_PERM_KRGRO,

                target.SIMPLE_MB_RF_O = source.SIMPLE_MB_RF_O,
                target.SIMPLE_MB_RF_G = source.SIMPLE_MB_RF_G,

                target.PSAT = source.PSAT,
                target.PSAT_TYPE = source.PSAT_TYPE,
                target.TOTAL_OIL_FVF = source.TOTAL_OIL_FVF,
                target.TOTAL_GOR = source.TOTAL_GOR,
                target.RESERVOIR_CLASS = source.RESERVOIR_CLASS,
                target.OIL_SAT = source.OIL_SAT,
                target.OIL_FVF = source.OIL_FVF,
                target.RS = source.RS,
                target.OIL_VISC = source.OIL_VISC,
                target.OIL_DENSITY = source.OIL_DENSITY,
                target.OIL_COMPRESSIBILITY = source.OIL_COMPRESSIBILITY,
                target.GAS_SAT = source.GAS_SAT,
                target.GAS_EXPANSION = source.GAS_EXPANSION,
                target.SOLUTION_CGR = source.SOLUTION_CGR,
                target.GAS_VISC = source.GAS_VISC,
                target.GAS_DENSITY = source.GAS_DENSITY,
                target.GAS_COMPRESSIBILITY = source.GAS_COMPRESSIBILITY,
                target.SURF_OIL_SG = source.SURF_OIL_SG,
                target.SURF_GAS_SG = source.SURF_GAS_SG,
                target.SURF_LIQ_API = source.SURF_LIQ_API,

                target.OIL_PEAK_RATE = source.OIL_PEAK_RATE,
                target.OIL_PEAK_DAY = source.OIL_PEAK_DAY,
                target.OIL_CUM30 = source.OIL_CUM30,
                target.OIL_CUM60 = source.OIL_CUM60,
                target.OIL_CUM90 = source.OIL_CUM90,
                target.OIL_CUM180 = source.OIL_CUM180,
                target.OIL_CUM365 = source.OIL_CUM365,
                target.GAS_PEAK_RATE = source.GAS_PEAK_RATE,
                target.GAS_PEAK_DAY = source.GAS_PEAK_DAY,
                target.GAS_CUM30 = source.GAS_CUM30,
                target.GAS_CUM60 = source.GAS_CUM60,
                target.GAS_CUM90 = source.GAS_CUM90,
                target.GAS_CUM180 = source.GAS_CUM180,
                target.GAS_CUM365 = source.GAS_CUM365,
                target.WATER_PEAK_RATE = source.WATER_PEAK_RATE,
                target.WATER_PEAK_DAY = source.WATER_PEAK_DAY,
                target.WATER_CUM30 = source.WATER_CUM30,
                target.WATER_CUM60 = source.WATER_CUM60,
                target.WATER_CUM90 = source.WATER_CUM90,
                target.WATER_CUM180 = source.WATER_CUM180,
                target.WATER_CUM365 = source.WATER_CUM365,
                target.GOR_CUM30 = source.GOR_CUM30,
                target.GOR_CUM60 = source.GOR_CUM60,
                target.GOR_CUM90 = source.GOR_CUM90,
                target.GOR_CUM180 = source.GOR_CUM180,
                target.GOR_CUM365 = source.GOR_CUM365,
                target.OGR_CUM30 = source.OGR_CUM30,
                target.OGR_CUM60 = source.OGR_CUM60,
                target.OGR_CUM90 = source.OGR_CUM90,
                target.OGR_CUM180 = source.OGR_CUM180,
                target.OGR_CUM365 = source.OGR_CUM365,
                target.WOR_CUM30 = source.WOR_CUM30,
                target.WOR_CUM60 = source.WOR_CUM60,
                target.WOR_CUM90 = source.WOR_CUM90,
                target.WOR_CUM180 = source.WOR_CUM180,
                target.WOR_CUM365 = source.WOR_CUM365,
                target.WGR_CUM30 = source.WGR_CUM30,
                target.WGR_CUM60 = source.WGR_CUM60,
                target.WGR_CUM90 = source.WGR_CUM90,
                target.WGR_CUM180 = source.WGR_CUM180,
                target.WGR_CUM365 = source.WGR_CUM365,
                target.FIRST_PROD_DATE = source.FIRST_PROD_DATE,
                target.DAYS_ONLINE = source.DAYS_ONLINE,
                target.MONTHS_ONLINE = source.MONTHS_ONLINE,
                target.YEARS_ONLINE = source.YEARS_ONLINE,
                target.OIL_IP30 = source.OIL_IP30,
                target.OIL_IP60 = source.OIL_IP60,
                target.OIL_IP90 = source.OIL_IP90,
                target.OIL_IP180 = source.OIL_IP180,
                target.OIL_IP365 = source.OIL_IP365,
                target.GAS_IP30 = source.GAS_IP30,
                target.GAS_IP60 = source.GAS_IP60,
                target.GAS_IP90 = source.GAS_IP90,
                target.GAS_IP180 = source.GAS_IP180,
                target.GAS_IP365 = source.GAS_IP365,
                target.WATER_IP30 = source.WATER_IP30,
                target.WATER_IP60 = source.WATER_IP60,
                target.WATER_IP90 = source.WATER_IP90,
                target.WATER_IP180 = source.WATER_IP180,
                target.WATER_IP365 = source.WATER_IP365,

                target.QC_PVT = source.QC_PVT,
                target.QC_DCA = source.QC_DCA,
                target.QC_BHP = source.QC_BHP,
                target.QC_FMB = source.QC_FMB,
                target.QC_ANALYTICAL_RTA = source.QC_ANALYTICAL_RTA,
                target.QC_NUMERICAL_RTA = source.QC_NUMERICAL_RTA,
                target.QC_NUMERICAL_MODEL = source.QC_NUMERICAL_MODEL,
                target.QC_IPR_VLP = source.QC_IPR_VLP,
                target.QC_PNR_DCA = source.QC_PNR_DCA,

                COMPUTER_RUN_DATE = source.COMPUTER_RUN_DATE
        WHEN NOT MATCHED THEN
            INSERT (
                EXTERNAL_ID,
                WELL_ID,
                WELL_NAME,
                UWI_API,
                PROJECT_ID,
                SCENARIO_NAME,
                DCA_EUR_O,
                DCA_EUR_G,
                DCA_EUR_W,
                DCA_EUR_O_LW,
                DCA_EUR_G_LW,
                DCA_EUR_W_LW,
                DCA_DATE_UPDATE,
                DCA_UPDATE_BY,

                PNR_DCA_EUR_O,
                PNR_DCA_EUR_G,
                PNR_DCA_EUR_W,
                PNR_DCA_EUR_O_LW,
                PNR_DCA_EUR_G_LW,
                PNR_DCA_EUR_W_LW,
                PNR_DCA_DATE_UPDATE,
                PNR_DCA_UPDATE_BY,

                BHP_DATE_UPDATE,
                BHP_UPDATE_BY,
                BHP_FOR_CALC,

                IPR_INIT_PRESS,
                IPR_PROD_INDEX_O,
                IPR_PROD_INDEX_G,

                MFMB_OOIP,
                MFMB_OGIP,
                MFMB_OWIP,
                MFMB_VP,
                MFMB_DATE_UPDATE,
                MFMB_UPDATE_BY,

                RFA_EUR_O,
                RFA_EUR_G,
                RFA_EUR_W,
                RFA_RF_O,
                RFA_RF_W,
                RFA_RF_G,
                RFA_DATE_UPDATE,
                RFA_UPDATE_BY,

                GMB_OOIP,
                GMB_OGIP,

                CLASSIC_RTA_TIME_FN,
                CLASSIC_RTA_PHASE,
                CLASSIC_RTA_LFP,
                CLASSIC_RTA_OOIP,
                CLASSIC_RTA_OGIP,
                CLASSIC_RTA_K,
                CLASSIC_RTA_XF,
                CLASSIC_RTA_T_ELF,
                CLASSIC_RTA_CT,
                CLASSIC_RTA_FCD,
                CLASSIC_RTA_SKIN,
                CLASSIC_RTA_EUR,
                CLASSIC_RTA_SLOPE,
                CLASSIC_RTA_INTERCEPT,
                CLASSIC_RTA_DATE_UPDATE,
                CLASSIC_RTA_UPDATE_BY,

                FRACTION_RTA_TIME_FN,
                FRACTION_RTA_PHASE,
                FRACTION_RTA_LFP,
                FRACTION_RTA_M,
                FRACTION_RTA_DELTA,
                FRACTION_RTA_CT,
                FRACTION_RTA_DATE_UPDATE,
                FRACTION_RTA_UPDATE_BY,

                NUMERIC_RTA_LFP,
                NUMERIC_RTA_OOIP,
                NUMERIC_RTA_OGIP,
                NUMERIC_RTA_K,
                NUMERIC_RTA_XF,
                NUMERIC_RTA_DATE_UPDATE,
                NUMERIC_RTA_UPDATE_BY,

                NUMERIC_MODEL_LFP,
                NUMERIC_MODEL_OOIP,
                NUMERIC_MODEL_OGIP,
                NUMERIC_MODEL_OWIP,
                NUMERIC_MODEL_K,
                NUMERIC_MODEL_XF,
                NUMERIC_MODEL_QO,
                NUMERIC_MODEL_QG,
                NUMERIC_MODEL_QW,
                NUMERIC_MODEL_RF_O,
                NUMERIC_MODEL_RF_G,
                NUMERIC_MODEL_RF_W,
                NUMERIC_MODEL_DATE_UPDATE,
                NUMERIC_MODEL_UPDATE_BY,

                REL_PERM_SWC,
                REL_PERM_SORW,
                REL_PERM_SORG,
                REL_PERM_SGC,
                REL_PERM_NW,
                REL_PERM_NOW,
                REL_PERM_NG,
                REL_PERM_NOG,
                REL_PERM_KRWRO,
                REL_PERM_KROCW,
                REL_PERM_KRGRO,

                SIMPLE_MB_RF_O,
                SIMPLE_MB_RF_G,

                PSAT,
                PSAT_TYPE,
                TOTAL_OIL_FVF,
                TOTAL_GOR,
                RESERVOIR_CLASS,
                OIL_SAT,
                OIL_FVF,
                RS,
                OIL_VISC,
                OIL_DENSITY,
                OIL_COMPRESSIBILITY,
                GAS_SAT,
                GAS_EXPANSION,
                SOLUTION_CGR,
                GAS_VISC,
                GAS_DENSITY,
                GAS_COMPRESSIBILITY,
                SURF_OIL_SG,
                SURF_GAS_SG,
                SURF_LIQ_API,

                OIL_PEAK_RATE,
                OIL_PEAK_DAY,
                OIL_CUM30,
                OIL_CUM60,
                OIL_CUM90,
                OIL_CUM180,
                OIL_CUM365,
                GAS_PEAK_RATE,
                GAS_PEAK_DAY,
                GAS_CUM30,
                GAS_CUM60,
                GAS_CUM90,
                GAS_CUM180,
                GAS_CUM365,
                WATER_PEAK_RATE,
                WATER_PEAK_DAY,
                WATER_CUM30,
                WATER_CUM60,
                WATER_CUM90,
                WATER_CUM180,
                WATER_CUM365,
                GOR_CUM30,
                GOR_CUM60,
                GOR_CUM90,
                GOR_CUM180,
                GOR_CUM365,
                OGR_CUM30,
                OGR_CUM60,
                OGR_CUM90,
                OGR_CUM180,
                OGR_CUM365,
                WOR_CUM30,
                WOR_CUM60,
                WOR_CUM90,
                WOR_CUM180,
                WOR_CUM365,
                WGR_CUM30,
                WGR_CUM60,
                WGR_CUM90,
                WGR_CUM180,
                WGR_CUM365,
                FIRST_PROD_DATE,
                DAYS_ONLINE,
                MONTHS_ONLINE,
                YEARS_ONLINE,
                OIL_IP30,
                OIL_IP60,
                OIL_IP90,
                OIL_IP180,
                OIL_IP365,
                GAS_IP30,
                GAS_IP60,
                GAS_IP90,
                GAS_IP180,
                GAS_IP365,
                WATER_IP30,
                WATER_IP60,
                WATER_IP90,
                WATER_IP180,
                WATER_IP365,

                QC_PVT,
                QC_DCA,
                QC_BHP,
                QC_FMB,
                QC_ANALYTICAL_RTA,
                QC_NUMERICAL_RTA,
                QC_NUMERICAL_MODEL,
                QC_IPR_VLP,
                QC_PNR_DCA,

                COMPUTER_RUN_DATE
            )
            VALUES (
                source.EXTERNAL_ID,
                source.WELL_ID,
                source.WELL_NAME,
                source.UWI_API,
                source.PROJECT_ID,
                source.SCENARIO_NAME,
                source.DCA_EUR_O,
                source.DCA_EUR_G,
                source.DCA_EUR_W,
                source.DCA_EUR_O_LW,
                source.DCA_EUR_G_LW,
                source.DCA_EUR_W_LW,
                source.DCA_DATE_UPDATE,
                source.DCA_UPDATE_BY,

                source.PNR_DCA_EUR_O,
                source.PNR_DCA_EUR_G,
                source.PNR_DCA_EUR_W,
                source.PNR_DCA_EUR_O_LW,
                source.PNR_DCA_EUR_G_LW,
                source.PNR_DCA_EUR_W_LW,
                source.PNR_DCA_DATE_UPDATE,
                source.PNR_DCA_UPDATE_BY,

                source.BHP_DATE_UPDATE,
                source.BHP_UPDATE_BY,
                source.BHP_FOR_CALC,

                source.IPR_INIT_PRESS,
                source.IPR_PROD_INDEX_O,
                source.IPR_PROD_INDEX_G,

                source.MFMB_OOIP,
                source.MFMB_OGIP,
                source.MFMB_OWIP,
                source.MFMB_VP,
                source.MFMB_DATE_UPDATE,
                source.MFMB_UPDATE_BY,

                source.RFA_EUR_O,
                source.RFA_EUR_G,
                source.RFA_EUR_W,
                source.RFA_RF_O,
                source.RFA_RF_W,
                source.RFA_RF_G,
                source.RFA_DATE_UPDATE,
                source.RFA_UPDATE_BY,

                source.GMB_OOIP,
                source.GMB_OGIP,

                source.CLASSIC_RTA_TIME_FN,
                source.CLASSIC_RTA_PHASE,
                source.CLASSIC_RTA_LFP,
                source.CLASSIC_RTA_OOIP,
                source.CLASSIC_RTA_OGIP,
                source.CLASSIC_RTA_K,
                source.CLASSIC_RTA_XF,
                source.CLASSIC_RTA_T_ELF,
                source.CLASSIC_RTA_CT,
                source.CLASSIC_RTA_FCD,
                source.CLASSIC_RTA_SKIN,
                source.CLASSIC_RTA_EUR,
                source.CLASSIC_RTA_SLOPE,
                source.CLASSIC_RTA_INTERCEPT,
                source.CLASSIC_RTA_DATE_UPDATE,
                source.CLASSIC_RTA_UPDATE_BY,

                source.FRACTION_RTA_TIME_FN,
                source.FRACTION_RTA_PHASE,
                source.FRACTION_RTA_LFP,
                source.FRACTION_RTA_M,
                source.FRACTION_RTA_DELTA,
                source.FRACTION_RTA_CT,
                source.FRACTION_RTA_DATE_UPDATE,
                source.FRACTION_RTA_UPDATE_BY,

                source.NUMERIC_RTA_LFP,
                source.NUMERIC_RTA_OOIP,
                source.NUMERIC_RTA_OGIP,
                source.NUMERIC_RTA_K,
                source.NUMERIC_RTA_XF,
                source.NUMERIC_RTA_DATE_UPDATE,
                source.NUMERIC_RTA_UPDATE_BY,

                source.NUMERIC_MODEL_LFP,
                source.NUMERIC_MODEL_OOIP,
                source.NUMERIC_MODEL_OGIP,
                source.NUMERIC_MODEL_OWIP,
                source.NUMERIC_MODEL_K,
                source.NUMERIC_MODEL_XF,
                source.NUMERIC_MODEL_QO,
                source.NUMERIC_MODEL_QG,
                source.NUMERIC_MODEL_QW,
                source.NUMERIC_MODEL_RF_O,
                source.NUMERIC_MODEL_RF_G,
                source.NUMERIC_MODEL_RF_W,
                source.NUMERIC_MODEL_DATE_UPDATE,
                source.NUMERIC_MODEL_UPDATE_BY,

                source.REL_PERM_SWC,
                source.REL_PERM_SORW,
                source.REL_PERM_SORG,
                source.REL_PERM_SGC,
                source.REL_PERM_NW,
                source.REL_PERM_NOW,
                source.REL_PERM_NG,
                source.REL_PERM_NOG,
                source.REL_PERM_KRWRO,
                source.REL_PERM_KROCW,
                source.REL_PERM_KRGRO,

                source.SIMPLE_MB_RF_O,
                source.SIMPLE_MB_RF_G,

                source.PSAT,
                source.PSAT_TYPE,
                source.TOTAL_OIL_FVF,
                source.TOTAL_GOR,
                source.RESERVOIR_CLASS,
                source.OIL_SAT,
                source.OIL_FVF,
                source.RS,
                source.OIL_VISC,
                source.OIL_DENSITY,
                source.OIL_COMPRESSIBILITY,
                source.GAS_SAT,
                source.GAS_EXPANSION,
                source.SOLUTION_CGR,
                source.GAS_VISC,
                source.GAS_DENSITY,
                source.GAS_COMPRESSIBILITY,
                source.SURF_OIL_SG,
                source.SURF_GAS_SG,
                source.SURF_LIQ_API,

                source.OIL_PEAK_RATE,
                source.OIL_PEAK_DAY,
                source.OIL_CUM30,
                source.OIL_CUM60,
                source.OIL_CUM90,
                source.OIL_CUM180,
                source.OIL_CUM365,
                source.GAS_PEAK_RATE,
                source.GAS_PEAK_DAY,
                source.GAS_CUM30,
                source.GAS_CUM60,
                source.GAS_CUM90,
                source.GAS_CUM180,
                source.GAS_CUM365,
                source.WATER_PEAK_RATE,
                source.WATER_PEAK_DAY,
                source.WATER_CUM30,
                source.WATER_CUM60,
                source.WATER_CUM90,
                source.WATER_CUM180,
                source.WATER_CUM365,
                source.GOR_CUM30,
                source.GOR_CUM60,
                source.GOR_CUM90,
                source.GOR_CUM180,
                source.GOR_CUM365,
                source.OGR_CUM30,
                source.OGR_CUM60,
                source.OGR_CUM90,
                source.OGR_CUM180,
                source.OGR_CUM365,
                source.WOR_CUM30,
                source.WOR_CUM60,
                source.WOR_CUM90,
                source.WOR_CUM180,
                source.WOR_CUM365,
                source.WGR_CUM30,
                source.WGR_CUM60,
                source.WGR_CUM90,
                source.WGR_CUM180,
                source.WGR_CUM365,
                source.FIRST_PROD_DATE,
                source.DAYS_ONLINE,
                source.MONTHS_ONLINE,
                source.YEARS_ONLINE,
                source.OIL_IP30,
                source.OIL_IP60,
                source.OIL_IP90,
                source.OIL_IP180,
                source.OIL_IP365,
                source.GAS_IP30,
                source.GAS_IP60,
                source.GAS_IP90,
                source.GAS_IP180,
                source.GAS_IP365,
                source.WATER_IP30,
                source.WATER_IP60,
                source.WATER_IP90,
                source.WATER_IP180,
                source.WATER_IP365,

                source.QC_PVT,
                source.QC_DCA,
                source.QC_BHP,
                source.QC_FMB,
                source.QC_ANALYTICAL_RTA,
                source.QC_NUMERICAL_RTA,
                source.QC_NUMERICAL_MODEL,
                source.QC_IPR_VLP,
                source.QC_PNR_DCA,

                source.COMPUTER_RUN_DATE
            );

    """

    conn.cursor().execute(merge_query)

    conn.close()


if __name__ == "__main__":
    snowflake_analysis_shareback()

Connect Snowflake to whitson+: DCA Shareback Example

What does the snowflake_dca_shareback.py file do?

This script connects to Snowflake and whitson+ domain, retrieves DCA for wells, processes the data into a summary of the analysis and its parameters, and loads the results into Snowflake tables (including temporary staging and merge logic). The file uses a helper class WhitsonConnection in whitson_connect.py provided here.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
import os
import sys
from datetime import datetime, timedelta

import pandas as pd
import snowflake.connector
from dotenv import load_dotenv

project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
repo_root = os.path.abspath(os.path.join(project_root, "../.."))
sys.path.extend({project_root, repo_root})

if not load_dotenv(os.path.join(repo_root, ".env")):
    print(f"Warning: .env file not found at {repo_root}/.env")

from aries_python_code import whitson_connect
from snowflake.connector.pandas_tools import write_pandas


def snowflake_dca_shareback():
    # ----------------------------------------------------------------------------------------------------------------
    # 1. WHITSON CONNECTION
    # ----------------------------------------------------------------------------------------------------------------

    CLIENT = "your_domain_here"
    CLIENT_ID = "your_client_id_here"
    CLIENT_SECRET = "your_client_secret_here"

    PROJECT_DICT = {
        ("Default"): 1,
    }

    PROJECT_ID_LIST = [value for value in PROJECT_DICT.values()]

    whitson_connection = whitson_connect.WhitsonConnection(
        CLIENT, CLIENT_ID, CLIENT_SECRET
    )

    whitson_connection.access_token = whitson_connection.get_access_token_smart()

    # ----------------------------------------------------------------------------------------------------------------
    # 2. SNOWFLAKE CONNECTION
    # ----------------------------------------------------------------------------------------------------------------

    TABLE_NAME = "ENTER_YOUR_TABLE_NAME_HERE"
    SCHEMA = "ENTER_YOUR_SCHEMA_HERE"

    conn_params = {
        "account": "YOUR_ACCOUNT",
        "user": "YOUR_USERNAME",
        "private_key_file": "YOUR_PRIVATE_KEY_FILE",
        "private_key_file_pwd": "YOUR PRIVATE_KEY_FILE_PASSWORD",
        "warehouse": "YOUR_WAREHOUSE",
        "database": "YOUR_DATABASE",
        "schema": "YOUR_SCHEMA",
        "role": "YOUR_ROLE",
        "authenticator": "YOUR_AUTHENTICATOR",
    }

    conn = snowflake.connector.connect(**conn_params)

    # ----------------------------------------------------------------------------------------------------------------
    # 3. CREATE SNOWFLAKE TABLE TO SHARE IF NOT CREATED BEFORE
    # ----------------------------------------------------------------------------------------------------------------

    create_table_query = f"""
    CREATE TABLE IF NOT EXISTS {SCHEMA}.{TABLE_NAME} (
        well_id INTEGER,
        well_name STRING,
        external_id STRING,
        date_updated DATE,
        updated_by STRING,
        eur FLOAT,
        fluid STRING,
        forecast_type STRING,
        a_lim FLOAT,
        cutoff_rate float,
        t_tot_prod_yrs FLOAT,
        terminal_rate FLOAT,
        dca_segments ARRAY
    );
    """
    conn.cursor().execute(create_table_query)

    # ---------------------------------------------------------------------------------------------------------------
    # 4. DROP AND CREATE SNOWFLAKE STG TABLE IF NOT CREATED BEFORE.
    # ---------------------------------------------------------------------------------------------------------------

    staging_table_query = f"CREATE OR REPLACE TEMP TABLE {SCHEMA}.{TABLE_NAME}_STG LIKE {SCHEMA}.{TABLE_NAME}"
    conn.cursor().execute(staging_table_query)

    # ---------------------------------------------------------------------------------------------------------------
    # 5. FETCH DCA DATA & SAVE TO RELEVANT DATAFRAME
    # ---------------------------------------------------------------------------------------------------------------

    chunk_size = 3000
    dca_summary = (
        pd.DataFrame()
    )  # Initialize an empty DataFrame to store all the processed data
    last_updated = (datetime.today() - timedelta(days=1)).strftime("%Y-%m-%d")
    # last_updated = None

    for project in PROJECT_ID_LIST:
        data = []  # Initialize an empty list to store all the JSON results
        whitson_wells = whitson_connection.get_wells_from_projects([project], 500)
        wellname_dict = {item["id"]: item["name"] for item in whitson_wells}
        well_id_dict = {item["id"]: item["external_id"] for item in whitson_wells}
        well_id_list = list(well_id_dict.keys())

        for i in range(0, len(well_id_list), chunk_size):
            well_chunk = well_id_list[i : i + chunk_size]
            chunk_data = whitson_connection.get_dca_fits_by_well_id_list(
                {"well_ids": well_chunk}, last_updated=last_updated  # YYYY-MM-DD format
            )
            data.extend(chunk_data)
            print(f"Well-{i} in dict {project}")

        processed_data = [
            {
                "well_id": item.get("well_id"),
                "well_name": wellname_dict.get(item.get("well_id")),  # Map well_name
                "external_id": well_id_dict.get(item.get("well_id")),  # Map external_id
                "date_updated": item.get("date_updated"),
                "updated_by": item.get("updated_by"),
                "eur": item.get("eur"),
                "fluid": item.get("fluid"),
                "a_lim": item.get("a_lim"),
                "cutoff_rate": item.get("cutoff_rate"),
                "forecast_type": item.get("forecast_type"),
                "t_tot_prod_yrs": item.get("t_tot_prod"),
                "terminal_rate": item.get("terminal_rate"),
                "dca_segments": item.get("dca_segments"), 
            }
            for item in data
        ]

        df = pd.DataFrame(processed_data)
        dca_summary = pd.concat([dca_summary, df], ignore_index=True)

    if dca_summary.empty:
        print("No Update from DCA Summary Shareback.")
        conn.close()
        return

    dca_summary = dca_summary.sort_values(by="well_id", ascending=True)
    dca_summary.drop_duplicates(subset=["well_id", "fluid"], inplace=True)
    dca_summary.columns = [col.upper() for col in dca_summary.columns]
    write_pandas(conn, dca_summary, f"{TABLE_NAME}")

    # ---------------------------------------------------------------------------------------------------------------
    # 10. FETCH AND LOAD DATA INTO STAGING TABLE
    # ---------------------------------------------------------------------------------------------------------------

    merge_query = f"""
        MERGE INTO {SCHEMA}.{TABLE_NAME} AS target
        USING {SCHEMA}.{TABLE_NAME}_STG AS source
        ON target.WELL_ID = source.WELL_ID
        AND target.FLUID = source.FLUID
        WHEN MATCHED THEN
            UPDATE SET
                target.WELL_ID = source.WELL_ID,
                target.WELL_NAME = source.WELL_NAME,
                target.EXTERNAL_ID = source.EXTERNAL_ID,
                target.DATE_UPDATED = source.DATE_UPDATED,
                target.UPDATED_BY = source.UPDATED_BY,
                target.EUR = source.EUR,
                target.FLUID = source.FLUID,
                target.FORECAST_TYPE = source.FORECAST_TYPE,
                target.A_LIM = source.A_LIM,
                target.CUTOFF_RATE = source.CUTOFF_RATE,
                target.T_TOT_PROD_YRS = source.T_TOT_PROD_YRS,
                target.TERMINAL_RATE = source.TERMINAL_RATE,
                target.DCA_SEGMENTS = source.DCA_SEGMENTS

        WHEN NOT MATCHED THEN
            INSERT (
                WELL_ID,
                WELL_NAME,
                EXTERNAL_ID,
                DATE_UPDATED,
                UPDATED_BY,
                EUR,
                FLUID,
                FORECAST_TYPE,
                A_LIM,
                CUTOFF_RATE,
                T_TOT_PROD_YRS,
                TERMINAL_RATE,
                DCA_SEGMENTS
            )
            VALUES (
                source.WELL_ID,
                source.WELL_NAME,
                source.EXTERNAL_ID,
                source.DATE_UPDATED,
                source.UPDATED_BY,
                source.EUR,
                source.FLUID,
                source.FORECAST_TYPE,
                source.A_LIM,
                source.CUTOFF_RATE,
                source.T_TOT_PROD_YRS,
                source.TERMINAL_RATE,
                source.DCA_SEGMENTS
            );

    """

    conn.cursor().execute(merge_query)

    conn.close()

if __name__ == "__main__":
    snowflake_dca_shareback()